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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_logisticregression.wasp
Title produced by softwareBias-Reduced Logistic Regression
Date of computationFri, 16 Dec 2011 16:10:01 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/16/t1324069819ib07tr1zf3kkgo5.htm/, Retrieved Sun, 05 May 2024 15:27:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156134, Retrieved Sun, 05 May 2024 15:27:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	41	38	13	12	14
1	1	39	32	16	11	18
1	1	30	35	19	15	11
1	0	31	33	15	6	12
1	1	34	37	14	13	16
1	1	35	29	13	10	18
1	1	39	31	19	12	14
1	1	34	36	15	14	14
1	1	36	35	14	12	15
1	1	37	38	15	9	15
1	0	38	31	16	10	17
1	1	36	34	16	12	19
1	0	38	35	16	12	10
1	1	39	38	16	11	16
1	1	33	37	17	15	18
1	0	32	33	15	12	14
1	0	36	32	15	10	14
1	1	38	38	20	12	17
1	0	39	38	18	11	14
1	1	32	32	16	12	16
1	0	32	33	16	11	18
1	1	31	31	16	12	11
1	1	39	38	19	13	14
1	1	37	39	16	11	12
1	0	39	32	17	12	17
1	1	41	32	17	13	9
1	0	36	35	16	10	16
1	1	33	37	15	14	14
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1	1	34	37	16	12	15
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1	0	32	33	10	7	16
1	0	29	31	10	9	9
1	0	36	33	14	12	15
1	1	29	31	16	10	17
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1	1	34	33	14	12	16
1	0	38	32	20	15	16
1	0	35	33	14	10	12
1	1	38	28	14	10	15
1	1	37	35	11	12	11
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1	1	32	38	16	14	16
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1	0	32	33	12	12	11
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1	1	39	34	16	12	16
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1	0	37	36	15	11	12
1	1	35	34	16	10	12
1	0	30	28	12	7	8
1	0	38	34	16	12	13
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1	1	31	35	14	11	14
1	1	34	31	16	12	15
1	0	35	37	17	13	10
1	1	36	35	18	14	11
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1	0	35	37	16	12	15
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1	1	34	39	18	14	15
1	0	38	41	18	14	15
1	0	34	27	16	12	13
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1	1	35	37	16	12	15
1	0	37	33	15	12	16
1	1	32	34	15	11	15
1	1	33	31	16	10	14
1	0	38	39	14	9	15
1	1	33	34	16	12	14
1	1	29	32	16	12	13
1	1	33	33	15	12	7
1	1	31	36	12	9	17
1	1	36	32	17	15	13
1	1	35	41	16	12	15
1	1	32	28	15	12	14
1	1	29	30	13	12	13
1	1	39	36	16	10	16
1	1	37	35	16	13	12
1	1	35	31	16	9	14
1	0	37	34	16	12	17
1	0	32	36	14	10	15
1	1	38	36	16	14	17
1	0	37	35	16	11	12
1	1	36	37	20	15	16
1	0	32	28	15	11	11
1	1	33	39	16	11	15
1	0	40	32	13	12	9
1	1	38	35	17	12	16
1	0	41	39	16	12	15
1	0	36	35	16	11	10
1	1	43	42	12	7	10
1	1	30	34	16	12	15
1	1	31	33	16	14	11
1	1	32	41	17	11	13
1	1	37	34	12	10	18
1	0	37	32	18	13	16
1	1	33	40	14	13	14
1	1	34	40	14	8	14
1	1	33	35	13	11	14
1	1	38	36	16	12	14
1	0	33	37	13	11	12
1	1	31	27	16	13	14
1	1	38	39	13	12	15
1	1	37	38	16	14	15
1	1	36	31	15	13	15
1	1	31	33	16	15	13
1	0	39	32	15	10	17
1	1	44	39	17	11	17
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1	1	35	33	12	11	15
1	0	32	33	16	10	13
1	0	28	32	10	11	9
1	1	40	37	16	8	15
1	0	27	30	12	11	15
1	0	37	38	14	12	15
1	1	32	29	15	12	16
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1	1	30	35	11	10	11
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1	0	31	35	11	9	13
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1	1	32	27	18	13	16
1	0	36	36	13	12	11
1	0	32	31	16	12	12
1	0	35	32	13	9	9
1	1	38	39	10	7	16
1	1	42	37	15	13	13
1	0	34	38	16	9	16
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1	1	38	34	14	8	9
1	1	33	31	10	8	13
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1	1	33	36	15	9	19
1	1	34	32	16	11	13
1	1	32	38	12	8	12
0	0	27	26	13	10	10
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0	1	34	39	15	10	10
0	0	24	30	10	8	11
0	0	30	33	14	11	14
0	1	26	25	11	12	12
0	1	34	38	13	12	9
0	0	27	37	16	12	9
0	0	37	31	12	5	11
0	1	36	37	16	12	16
0	0	41	35	12	10	9
0	1	29	25	9	7	13
0	1	36	28	12	12	16
0	0	32	35	15	11	13
0	1	37	33	12	8	9
0	0	30	30	12	9	12
0	1	31	31	14	10	16
0	1	38	37	12	9	11
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0	0	35	30	11	6	13
0	0	31	36	19	15	15
0	0	38	32	15	12	14
0	1	22	28	8	12	16
0	1	32	36	16	12	13
0	0	36	34	17	11	14
0	1	39	31	12	7	15
0	0	28	28	11	7	13
0	0	32	36	11	5	11
0	1	32	36	14	12	11
0	1	38	40	16	12	14
0	1	32	33	12	3	15
0	1	35	37	16	11	11
0	1	32	32	13	10	15
0	0	37	38	15	12	12
0	1	34	31	16	9	14
0	1	33	37	16	12	14
0	0	33	33	14	9	8
0	0	30	30	16	12	9
0	0	24	30	14	10	15
0	0	34	31	11	9	17
0	0	34	32	12	12	13
0	1	33	34	15	8	15
0	1	34	36	15	11	15
0	1	35	37	16	11	14
0	0	35	36	16	12	16
0	0	36	33	11	10	13
0	0	34	33	15	10	16
0	1	34	33	12	12	9
0	0	41	44	12	12	16
0	0	32	39	15	11	11
0	0	30	32	15	8	10
0	1	35	35	16	12	11
0	0	28	25	14	10	15
0	1	33	35	17	11	17
0	1	39	34	14	10	14
0	0	36	35	13	8	8
0	1	36	39	15	12	15
0	0	35	33	13	12	11
0	0	38	36	14	10	16
0	1	33	32	15	12	10
0	0	31	32	12	9	15
0	1	32	36	8	6	16
0	0	31	32	14	10	19
0	0	33	34	14	9	12
0	0	34	33	11	9	8
0	0	34	35	12	9	11
0	1	34	30	13	6	14
0	0	33	38	10	10	9
0	0	32	34	16	6	15
0	1	41	33	18	14	13
0	1	34	32	13	10	16
0	0	36	31	11	10	11
0	0	37	30	4	6	12
0	0	36	27	13	12	13
0	1	29	31	16	12	10
0	0	37	30	10	7	11
0	0	27	32	12	8	12
0	0	35	35	12	11	8
0	0	28	28	10	3	12
0	0	35	33	13	6	12
0	0	29	35	12	8	11
0	0	32	35	14	9	13
0	1	36	32	10	9	14
0	1	19	21	12	8	10
0	1	21	20	12	9	12
0	0	31	34	11	7	15
0	0	33	32	10	7	13
0	1	36	34	12	6	13
0	1	33	32	16	9	13
0	0	37	33	12	10	12
0	0	34	33	14	11	12
0	0	35	37	16	12	9
0	1	31	32	14	8	9
0	1	37	34	13	11	15
0	1	35	30	4	3	10
0	1	27	30	15	11	14
0	0	34	38	11	12	15
0	0	40	36	11	7	7
0	0	29	32	14	9	14
0	0	38	34	15	12	8
0	1	34	33	14	8	10
0	0	21	27	13	11	13
0	0	36	32	11	8	13
0	1	38	34	15	10	13
0	0	30	29	11	8	8
0	0	35	35	13	7	12
0	1	30	27	13	8	13
0	1	36	33	16	10	12
0	0	34	38	13	8	10
0	1	35	36	16	12	13
0	0	34	33	16	14	12
0	0	32	39	12	7	9
0	1	33	29	7	6	15
0	0	33	32	16	11	13
0	1	26	34	5	4	13
0	0	35	38	16	9	13
0	0	21	17	4	5	15
0	0	38	35	12	9	15
0	0	35	32	15	11	14
0	1	33	34	14	12	15
0	0	37	36	11	9	11
0	0	38	31	16	12	15
0	1	34	35	15	10	14
0	0	27	29	12	9	13
0	1	16	22	6	6	12
0	0	40	41	16	10	16
0	0	36	36	10	9	16
0	1	42	42	15	13	9
0	1	30	33	14	12	14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156134&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156134&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156134&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.wessa.net






Coefficients of Bias-Reduced Logistic Regression
VariableParameterS.E.t-stat2-sided p-value
(Intercept)-8.006338889241651.62617234730032-4.923425799567511.45237323034841e-06
Gender0.436277628321170.2705764733600211.612400453385580.107997337681812
Connected0.05245179055621120.04009250633448571.308269184236420.191851138242824
Separate-0.001835511924690960.0409929738664156-0.04477625679640540.964317452968626
Learning0.1854670940647420.07208738884645832.57280915611710.0106011684875886
Software0.1361537068784560.07408922608456191.837699137564970.0671624246742966
Happiness0.1659806997338360.05587457543203552.970594379472840.00322906161933467

\begin{tabular}{lllllllll}
\hline
Coefficients of Bias-Reduced Logistic Regression \tabularnewline
Variable & Parameter & S.E. & t-stat & 2-sided p-value \tabularnewline
(Intercept) & -8.00633888924165 & 1.62617234730032 & -4.92342579956751 & 1.45237323034841e-06 \tabularnewline
Gender & 0.43627762832117 & 0.270576473360021 & 1.61240045338558 & 0.107997337681812 \tabularnewline
Connected & 0.0524517905562112 & 0.0400925063344857 & 1.30826918423642 & 0.191851138242824 \tabularnewline
Separate & -0.00183551192469096 & 0.0409929738664156 & -0.0447762567964054 & 0.964317452968626 \tabularnewline
Learning & 0.185467094064742 & 0.0720873888464583 & 2.5728091561171 & 0.0106011684875886 \tabularnewline
Software & 0.136153706878456 & 0.0740892260845619 & 1.83769913756497 & 0.0671624246742966 \tabularnewline
Happiness & 0.165980699733836 & 0.0558745754320355 & 2.97059437947284 & 0.00322906161933467 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156134&T=1

[TABLE]
[ROW][C]Coefficients of Bias-Reduced Logistic Regression[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.E.[/C][C]t-stat[/C][C]2-sided p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]-8.00633888924165[/C][C]1.62617234730032[/C][C]-4.92342579956751[/C][C]1.45237323034841e-06[/C][/ROW]
[ROW][C]Gender[/C][C]0.43627762832117[/C][C]0.270576473360021[/C][C]1.61240045338558[/C][C]0.107997337681812[/C][/ROW]
[ROW][C]Connected[/C][C]0.0524517905562112[/C][C]0.0400925063344857[/C][C]1.30826918423642[/C][C]0.191851138242824[/C][/ROW]
[ROW][C]Separate[/C][C]-0.00183551192469096[/C][C]0.0409929738664156[/C][C]-0.0447762567964054[/C][C]0.964317452968626[/C][/ROW]
[ROW][C]Learning[/C][C]0.185467094064742[/C][C]0.0720873888464583[/C][C]2.5728091561171[/C][C]0.0106011684875886[/C][/ROW]
[ROW][C]Software[/C][C]0.136153706878456[/C][C]0.0740892260845619[/C][C]1.83769913756497[/C][C]0.0671624246742966[/C][/ROW]
[ROW][C]Happiness[/C][C]0.165980699733836[/C][C]0.0558745754320355[/C][C]2.97059437947284[/C][C]0.00322906161933467[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156134&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156134&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Coefficients of Bias-Reduced Logistic Regression
VariableParameterS.E.t-stat2-sided p-value
(Intercept)-8.006338889241651.62617234730032-4.923425799567511.45237323034841e-06
Gender0.436277628321170.2705764733600211.612400453385580.107997337681812
Connected0.05245179055621120.04009250633448571.308269184236420.191851138242824
Separate-0.001835511924690960.0409929738664156-0.04477625679640540.964317452968626
Learning0.1854670940647420.07208738884645832.57280915611710.0106011684875886
Software0.1361537068784560.07408922608456191.837699137564970.0671624246742966
Happiness0.1659806997338360.05587457543203552.970594379472840.00322906161933467






Summary of Bias-Reduced Logistic Regression
Deviance333.091315741601
Penalized deviance296.6826000007
Residual Degrees of Freedom281
ROC Area0.76587147030185
Hosmer–Lemeshow test
Chi-square13.0714260751391
Degrees of Freedom8
P(>Chi)0.109415581770519

\begin{tabular}{lllllllll}
\hline
Summary of Bias-Reduced Logistic Regression \tabularnewline
Deviance & 333.091315741601 \tabularnewline
Penalized deviance & 296.6826000007 \tabularnewline
Residual Degrees of Freedom & 281 \tabularnewline
ROC Area & 0.76587147030185 \tabularnewline
Hosmer–Lemeshow test \tabularnewline
Chi-square & 13.0714260751391 \tabularnewline
Degrees of Freedom & 8 \tabularnewline
P(>Chi) & 0.109415581770519 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156134&T=2

[TABLE]
[ROW][C]Summary of Bias-Reduced Logistic Regression[/C][/ROW]
[ROW][C]Deviance[/C][C]333.091315741601[/C][/ROW]
[ROW][C]Penalized deviance[/C][C]296.6826000007[/C][/ROW]
[ROW][C]Residual Degrees of Freedom[/C][C]281[/C][/ROW]
[ROW][C]ROC Area[/C][C]0.76587147030185[/C][/ROW]
[ROW][C]Hosmer–Lemeshow test[/C][/ROW]
[ROW][C]Chi-square[/C][C]13.0714260751391[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]8[/C][/ROW]
[ROW][C]P(>Chi)[/C][C]0.109415581770519[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156134&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156134&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of Bias-Reduced Logistic Regression
Deviance333.091315741601
Penalized deviance296.6826000007
Residual Degrees of Freedom281
ROC Area0.76587147030185
Hosmer–Lemeshow test
Chi-square13.0714260751391
Degrees of Freedom8
P(>Chi)0.109415581770519






Fit of Logistic Regression
IndexActualFittedError
110.7066894140767150.293310585923285
210.8664165087665550.133583491233445
310.7910419730586520.208958026941348
410.2993891790970860.700610820902914
510.7627135328240380.237286467175962
610.7256739505471560.274326049452844
710.8699036090936860.130096390906314
810.7611708309301370.238829169069863
910.725926922934130.27407307706587
1010.6895477420401630.310452257959837
1110.7466095449925780.253390455007422
1210.881920842267830.118079157732169
1310.5457990680959730.454200931904027
1410.821517780280150.178482219719849
1510.9068556362870320.0931443637129676
1610.586890896437420.41310910356258
1710.5721093483030350.427890651696965
1810.9254089752150390.0745910247849615
1910.755720724687010.24427927531299
2010.7869551981680960.213044801831904
2110.7435235115879450.256476488412055
2210.6049537258942980.395046274105702
2310.8832333452694440.116766654730556
2410.6804852487214650.319514751278535
2510.8304755800802460.169524419919754
2610.7187947166738270.281205283326173
2710.6904843011439740.309515698856026
2810.7511625105092380.248837489490762
2910.7669742770842210.233025722915779
3010.3776145048503090.622385495149691
3110.7447082393097660.255291760690234
3210.2357193710274020.764280628972598
3310.7490406726659620.250959327334038
3410.7749392302811820.225060769718818
3510.568582525753090.43141747424691
3610.2839370750096240.716062924990376
3710.1225762004226510.877423799577349
3810.6321491887599430.367850811240057
3910.7397793930710930.260220606928907
4010.5635695089606620.436430491039338
4110.6669365828737890.333063417126211
4210.7386189239809150.261381076019085
4310.9117692539833320.0882307460166681
4410.4301465321402530.569853467859747
4510.6941300510095490.305869948990451
4610.451696687793950.54830331220605
4710.7699041060926750.230095893907325
4810.7042977361389880.295702263861012
4910.8227789750073540.177221024992646
5010.578404143716630.42159585628337
5110.82749304970110.1725069502989
5210.4747363406462090.525263659353791
5310.3310995462033020.668900453796698
5410.7053259603795030.294674039620497
5510.1145710365110440.885428963488956
5610.5522050768375650.447794923162435
5710.8415971986216970.158402801378303
5810.7270410936733470.272958906326653
5910.5348843610775930.465115638922407
6010.6281113489662460.371888651033754
6110.1215692698693550.878430730130645
6210.6645169228843740.335483077115626
6310.7002460494164820.299753950583518
6410.6010066424510370.398993357548963
6510.7768541849903760.223145815009624
6610.585236030089990.41476396991001
6710.789897480905190.21010251909481
6810.5855314674472150.414468532552785
6910.6794615048750140.320538495124986
7010.7011098201831580.298890179816842
7110.3075456283530250.692454371646975
7210.6761459670204680.323854032979532
7310.8671492440970510.132850755902949
7410.8383284618799480.161671538120052
7510.6192887083844920.380711291615508
7610.6879570501666410.312042949833359
7710.8655164667980240.134483533201976
7810.685531842316130.31446815768387
7910.4850138844502570.514986115549743
8010.6556312821548180.344368717845182
8110.6790741558104270.320925844189573
8210.7839551777521870.216044822247813
8310.7201785723475050.279821427652495
8410.6932582324669880.306741767533012
8510.6806340851323260.319365914867674
8610.556477291763690.44352270823631
8710.7356515025399420.264348497460058
8810.6573194306837320.342680569316268
8910.4201863941039020.579813605896098
9010.5652571867896580.434742813210342
9110.8337529383420830.166247061657917
9210.7827090668100560.217290933189944
9310.6892429475607980.310757052439202
9410.5246403012690350.475359698730965
9510.8012590222803020.198740977719698
9610.7380102173280020.261989782671998
9710.673803200474420.326196799525581
9810.7849855101929910.215014489807009
9910.5134534671362820.486546532863718
10010.8861824016412650.113817598358735
10110.5810455916715910.418954408328409
10210.934479580764350.0655204192356509
10310.4319766376199190.568023362380081
10410.7396475769782240.260352423021776
10510.3945417497346550.605458250265345
10610.858311991199780.14168800880022
10710.7619913238328650.238008676167135
10810.4856674104607030.514332589539297
10910.3651135660725850.634886433927415
11010.7373254432418010.262674556758199
11110.6670306273528570.332969372647143
11210.698785358263830.30121464173617
11310.7074522794153850.292547720584615
11410.8374992917866510.162500708213349
11510.6851830463351040.314816953664896
11610.5372751905953770.462724809404623
11710.5815398183501180.418460181649882
11810.7828029732514350.217197026748565
11910.3910710477175130.608928952282487
12010.7441377430051970.255862256994803
12110.708094825946490.291905174053509
12210.8408065437730480.159193456226952
12310.786342372868150.21365762713185
12410.761859361696560.238140638303441
12510.7202616679961950.279738332003805
12610.8945926237617140.105407376238286
12710.7783009539574480.221699046042552
12810.603049073984470.39695092601553
12910.5245567729304030.475443227069597
13010.1480172925963480.851982707403652
13110.7323366103539230.267663389646077
13210.3936012334063220.606398766593678
13310.6421532599757510.357846740024249
13410.7552309124204190.244769087579581
13510.2467862017666980.753213798233302
13610.5783993614929930.421600638507007
13710.3029503606339610.69704963936604
13810.5019723105000390.498027689499961
13910.2647731233700080.735226876629992
14010.6439161519654620.356083848034538
14110.5405064969764360.459493503023564
14210.8112611252477480.188738874752252
14310.6300251293877210.369974870612279
14410.5176679616882090.482332038311791
14510.8609178465782160.139082153421784
14610.4222732338096370.577726766190363
14710.5518884939488660.448111506051134
14810.2499309256735520.750069074326448
14910.4538715191853910.546128480814609
15010.7815554165553110.218444583444689
15110.6354849571901060.364515042809894
15210.4925831907099210.507416809290079
15310.3870557240091170.612944275990883
15410.3112239676593260.688776032340674
15510.3994412817501470.600558718249853
15610.7783009539574480.221699046042552
15710.6851360117574990.314863988242501
15810.341919882378330.65808011762167
15900.230507542830998-0.230507542830998
16000.312277733229373-0.312277733229373
16100.837676529831054-0.837676529831054
16200.486269735310215-0.486269735310215
16300.115794443940548-0.115794443940548
16400.481159630055892-0.481159630055892
16500.357449437750225-0.357449437750225
16600.421234711859212-0.421234711859212
16700.362874363298249-0.362874363298249
16800.199349948263396-0.199349948263396
16900.818660490821522-0.818660490821522
17000.301726496478414-0.301726496478414
17100.211681694885052-0.211681694885052
17200.686100160754612-0.686100160754612
17300.51132850453606-0.51132850453606
17400.292917609249984-0.292917609249984
17500.26016836848418-0.26016836848418
17600.648581752657515-0.648581752657515
17700.409016893394024-0.409016893394024
17800.764439040599534-0.764439040599534
17900.2295626780556-0.2295626780556
18000.8333390502955-0.8333390502955
18100.660982012412751-0.660982012412751
18200.33308969095055-0.33308969095055
18300.690270602166589-0.690270602166589
18400.688663691775831-0.688663691775831
18500.521748586779815-0.521748586779815
18600.191836644901513-0.191836644901513
18700.136194248480729-0.136194248480729
18800.524602392095673-0.524602392095673
18900.78155206840505-0.78155206840505
19000.303983676057041-0.303983676057041
19100.619821215111079-0.619821215111079
19200.577368347017141-0.577368347017141
19300.567644505528032-0.567644505528032
19400.662171320139291-0.662171320139291
19500.7345792668584-0.7345792668584
19600.233933262717314-0.233933262717314
19700.403065997390284-0.403065997390284
19800.4122251242698-0.4122251242698
19900.451977092980775-0.451977092980775
20000.434253978823333-0.434253978823333
20100.612868741633981-0.612868741633981
20200.71435471734017-0.71435471734017
20300.728441857977288-0.728441857977288
20400.735051390345038-0.735051390345038
20500.349958388140841-0.349958388140841
20600.626138169229684-0.626138169229684
20700.378952578730195-0.378952578730195
20800.6407366409968-0.6407366409968
20900.427029368285419-0.427029368285419
21000.2767824032728-0.2767824032728
21100.652175164401947-0.652175164401947
21200.466104649043583-0.466104649043583
21300.827627905029396-0.827627905029396
21400.667068804508981-0.667068804508981
21500.205189485032229-0.205189485032229
21600.759908808874384-0.759908808874384
21700.410864262992882-0.410864262992882
21800.630536316687389-0.630536316687389
21900.544325664205685-0.544325664205685
22000.377923618593935-0.377923618593935
22100.268679575025636-0.268679575025636
22200.662094028530696-0.662094028530696
22300.371883241870597-0.371883241870597
22400.155751787278571-0.155751787278571
22500.266892823459304-0.266892823459304
22600.427993712263745-0.427993712263745
22700.163126773529052-0.163126773529052
22800.47098693992073-0.47098693992073
22900.872383443940895-0.872383443940895
23000.64172608259535-0.64172608259535
23100.279385353706797-0.279385353706797
23200.0710857865921835-0.0710857865921835
23300.508757242070833-0.508757242070833
23400.538738403649526-0.538738403649526
23500.18434936939502-0.18434936939502
23600.207136390660684-0.207136390660684
23700.234400564859635-0.234400564859635
23800.0883312604504473-0.0883312604504473
23900.266718621040396-0.266718621040396
24000.196414336996727-0.196414336996727
24100.39832414775847-0.39832414775847
24200.416599379008702-0.416599379008702
24300.162821716876137-0.162821716876137
24400.256826835994326-0.256826835994326
24500.276914974467596-0.276914974467596
24600.202834781054739-0.202834781054739
24700.36727436386376-0.36727436386376
24800.611285127777491-0.611285127777491
24900.366494785448559-0.366494785448559
25000.450772141845891-0.450772141845891
25100.464237205347947-0.464237205347947
25200.30508547572357-0.30508547572357
25300.669676233680557-0.669676233680557
25400.0483754807588189-0.0483754807588189
25500.597365201257531-0.597365201257531
25600.467786071578439-0.467786071578439
25700.139521872571761-0.139521872571761
25800.401715835774213-0.401715835774213
25900.417782832003998-0.417782832003998
26000.377142113418853-0.377142113418853
26100.291543793843981-0.291543793843981
26200.291172974065719-0.291172974065719
26300.659707710572722-0.659707710572722
26400.116211935787898-0.116211935787898
26500.293415611144785-0.293415611144785
26600.404195145877812-0.404195145877812
26700.640701528938753-0.640701528938753
26800.243678173524166-0.243678173524166
26900.722869473919669-0.722869473919669
27000.641491575935516-0.641491575935516
27100.150976947102947-0.150976947102947
27200.216279716343484-0.216279716343484
27300.571689397840238-0.571689397840238
27400.0666688203403835-0.0666688203403835
27500.527554626959814-0.527554626959814
27600.0463662623974217-0.0463662623974217
27700.465874441957976-0.465874441957976
27800.592464855267995-0.592464855267995
27900.693925212798238-0.693925212798238
28000.261074369298987-0.261074369298987
28100.73515892394614-0.73515892394614
28200.649383399576935-0.649383399576935
28300.262186925042768-0.262186925042768
28400.0546957578366119-0.0546957578366119
28500.731290225372777-0.731290225372777
28600.389739497085831-0.389739497085831
28700.646034473114111-0.646034473114111
28800.621762094593828-0.621762094593828

\begin{tabular}{lllllllll}
\hline
Fit of Logistic Regression \tabularnewline
Index & Actual & Fitted & Error \tabularnewline
1 & 1 & 0.706689414076715 & 0.293310585923285 \tabularnewline
2 & 1 & 0.866416508766555 & 0.133583491233445 \tabularnewline
3 & 1 & 0.791041973058652 & 0.208958026941348 \tabularnewline
4 & 1 & 0.299389179097086 & 0.700610820902914 \tabularnewline
5 & 1 & 0.762713532824038 & 0.237286467175962 \tabularnewline
6 & 1 & 0.725673950547156 & 0.274326049452844 \tabularnewline
7 & 1 & 0.869903609093686 & 0.130096390906314 \tabularnewline
8 & 1 & 0.761170830930137 & 0.238829169069863 \tabularnewline
9 & 1 & 0.72592692293413 & 0.27407307706587 \tabularnewline
10 & 1 & 0.689547742040163 & 0.310452257959837 \tabularnewline
11 & 1 & 0.746609544992578 & 0.253390455007422 \tabularnewline
12 & 1 & 0.88192084226783 & 0.118079157732169 \tabularnewline
13 & 1 & 0.545799068095973 & 0.454200931904027 \tabularnewline
14 & 1 & 0.82151778028015 & 0.178482219719849 \tabularnewline
15 & 1 & 0.906855636287032 & 0.0931443637129676 \tabularnewline
16 & 1 & 0.58689089643742 & 0.41310910356258 \tabularnewline
17 & 1 & 0.572109348303035 & 0.427890651696965 \tabularnewline
18 & 1 & 0.925408975215039 & 0.0745910247849615 \tabularnewline
19 & 1 & 0.75572072468701 & 0.24427927531299 \tabularnewline
20 & 1 & 0.786955198168096 & 0.213044801831904 \tabularnewline
21 & 1 & 0.743523511587945 & 0.256476488412055 \tabularnewline
22 & 1 & 0.604953725894298 & 0.395046274105702 \tabularnewline
23 & 1 & 0.883233345269444 & 0.116766654730556 \tabularnewline
24 & 1 & 0.680485248721465 & 0.319514751278535 \tabularnewline
25 & 1 & 0.830475580080246 & 0.169524419919754 \tabularnewline
26 & 1 & 0.718794716673827 & 0.281205283326173 \tabularnewline
27 & 1 & 0.690484301143974 & 0.309515698856026 \tabularnewline
28 & 1 & 0.751162510509238 & 0.248837489490762 \tabularnewline
29 & 1 & 0.766974277084221 & 0.233025722915779 \tabularnewline
30 & 1 & 0.377614504850309 & 0.622385495149691 \tabularnewline
31 & 1 & 0.744708239309766 & 0.255291760690234 \tabularnewline
32 & 1 & 0.235719371027402 & 0.764280628972598 \tabularnewline
33 & 1 & 0.749040672665962 & 0.250959327334038 \tabularnewline
34 & 1 & 0.774939230281182 & 0.225060769718818 \tabularnewline
35 & 1 & 0.56858252575309 & 0.43141747424691 \tabularnewline
36 & 1 & 0.283937075009624 & 0.716062924990376 \tabularnewline
37 & 1 & 0.122576200422651 & 0.877423799577349 \tabularnewline
38 & 1 & 0.632149188759943 & 0.367850811240057 \tabularnewline
39 & 1 & 0.739779393071093 & 0.260220606928907 \tabularnewline
40 & 1 & 0.563569508960662 & 0.436430491039338 \tabularnewline
41 & 1 & 0.666936582873789 & 0.333063417126211 \tabularnewline
42 & 1 & 0.738618923980915 & 0.261381076019085 \tabularnewline
43 & 1 & 0.911769253983332 & 0.0882307460166681 \tabularnewline
44 & 1 & 0.430146532140253 & 0.569853467859747 \tabularnewline
45 & 1 & 0.694130051009549 & 0.305869948990451 \tabularnewline
46 & 1 & 0.45169668779395 & 0.54830331220605 \tabularnewline
47 & 1 & 0.769904106092675 & 0.230095893907325 \tabularnewline
48 & 1 & 0.704297736138988 & 0.295702263861012 \tabularnewline
49 & 1 & 0.822778975007354 & 0.177221024992646 \tabularnewline
50 & 1 & 0.57840414371663 & 0.42159585628337 \tabularnewline
51 & 1 & 0.8274930497011 & 0.1725069502989 \tabularnewline
52 & 1 & 0.474736340646209 & 0.525263659353791 \tabularnewline
53 & 1 & 0.331099546203302 & 0.668900453796698 \tabularnewline
54 & 1 & 0.705325960379503 & 0.294674039620497 \tabularnewline
55 & 1 & 0.114571036511044 & 0.885428963488956 \tabularnewline
56 & 1 & 0.552205076837565 & 0.447794923162435 \tabularnewline
57 & 1 & 0.841597198621697 & 0.158402801378303 \tabularnewline
58 & 1 & 0.727041093673347 & 0.272958906326653 \tabularnewline
59 & 1 & 0.534884361077593 & 0.465115638922407 \tabularnewline
60 & 1 & 0.628111348966246 & 0.371888651033754 \tabularnewline
61 & 1 & 0.121569269869355 & 0.878430730130645 \tabularnewline
62 & 1 & 0.664516922884374 & 0.335483077115626 \tabularnewline
63 & 1 & 0.700246049416482 & 0.299753950583518 \tabularnewline
64 & 1 & 0.601006642451037 & 0.398993357548963 \tabularnewline
65 & 1 & 0.776854184990376 & 0.223145815009624 \tabularnewline
66 & 1 & 0.58523603008999 & 0.41476396991001 \tabularnewline
67 & 1 & 0.78989748090519 & 0.21010251909481 \tabularnewline
68 & 1 & 0.585531467447215 & 0.414468532552785 \tabularnewline
69 & 1 & 0.679461504875014 & 0.320538495124986 \tabularnewline
70 & 1 & 0.701109820183158 & 0.298890179816842 \tabularnewline
71 & 1 & 0.307545628353025 & 0.692454371646975 \tabularnewline
72 & 1 & 0.676145967020468 & 0.323854032979532 \tabularnewline
73 & 1 & 0.867149244097051 & 0.132850755902949 \tabularnewline
74 & 1 & 0.838328461879948 & 0.161671538120052 \tabularnewline
75 & 1 & 0.619288708384492 & 0.380711291615508 \tabularnewline
76 & 1 & 0.687957050166641 & 0.312042949833359 \tabularnewline
77 & 1 & 0.865516466798024 & 0.134483533201976 \tabularnewline
78 & 1 & 0.68553184231613 & 0.31446815768387 \tabularnewline
79 & 1 & 0.485013884450257 & 0.514986115549743 \tabularnewline
80 & 1 & 0.655631282154818 & 0.344368717845182 \tabularnewline
81 & 1 & 0.679074155810427 & 0.320925844189573 \tabularnewline
82 & 1 & 0.783955177752187 & 0.216044822247813 \tabularnewline
83 & 1 & 0.720178572347505 & 0.279821427652495 \tabularnewline
84 & 1 & 0.693258232466988 & 0.306741767533012 \tabularnewline
85 & 1 & 0.680634085132326 & 0.319365914867674 \tabularnewline
86 & 1 & 0.55647729176369 & 0.44352270823631 \tabularnewline
87 & 1 & 0.735651502539942 & 0.264348497460058 \tabularnewline
88 & 1 & 0.657319430683732 & 0.342680569316268 \tabularnewline
89 & 1 & 0.420186394103902 & 0.579813605896098 \tabularnewline
90 & 1 & 0.565257186789658 & 0.434742813210342 \tabularnewline
91 & 1 & 0.833752938342083 & 0.166247061657917 \tabularnewline
92 & 1 & 0.782709066810056 & 0.217290933189944 \tabularnewline
93 & 1 & 0.689242947560798 & 0.310757052439202 \tabularnewline
94 & 1 & 0.524640301269035 & 0.475359698730965 \tabularnewline
95 & 1 & 0.801259022280302 & 0.198740977719698 \tabularnewline
96 & 1 & 0.738010217328002 & 0.261989782671998 \tabularnewline
97 & 1 & 0.67380320047442 & 0.326196799525581 \tabularnewline
98 & 1 & 0.784985510192991 & 0.215014489807009 \tabularnewline
99 & 1 & 0.513453467136282 & 0.486546532863718 \tabularnewline
100 & 1 & 0.886182401641265 & 0.113817598358735 \tabularnewline
101 & 1 & 0.581045591671591 & 0.418954408328409 \tabularnewline
102 & 1 & 0.93447958076435 & 0.0655204192356509 \tabularnewline
103 & 1 & 0.431976637619919 & 0.568023362380081 \tabularnewline
104 & 1 & 0.739647576978224 & 0.260352423021776 \tabularnewline
105 & 1 & 0.394541749734655 & 0.605458250265345 \tabularnewline
106 & 1 & 0.85831199119978 & 0.14168800880022 \tabularnewline
107 & 1 & 0.761991323832865 & 0.238008676167135 \tabularnewline
108 & 1 & 0.485667410460703 & 0.514332589539297 \tabularnewline
109 & 1 & 0.365113566072585 & 0.634886433927415 \tabularnewline
110 & 1 & 0.737325443241801 & 0.262674556758199 \tabularnewline
111 & 1 & 0.667030627352857 & 0.332969372647143 \tabularnewline
112 & 1 & 0.69878535826383 & 0.30121464173617 \tabularnewline
113 & 1 & 0.707452279415385 & 0.292547720584615 \tabularnewline
114 & 1 & 0.837499291786651 & 0.162500708213349 \tabularnewline
115 & 1 & 0.685183046335104 & 0.314816953664896 \tabularnewline
116 & 1 & 0.537275190595377 & 0.462724809404623 \tabularnewline
117 & 1 & 0.581539818350118 & 0.418460181649882 \tabularnewline
118 & 1 & 0.782802973251435 & 0.217197026748565 \tabularnewline
119 & 1 & 0.391071047717513 & 0.608928952282487 \tabularnewline
120 & 1 & 0.744137743005197 & 0.255862256994803 \tabularnewline
121 & 1 & 0.70809482594649 & 0.291905174053509 \tabularnewline
122 & 1 & 0.840806543773048 & 0.159193456226952 \tabularnewline
123 & 1 & 0.78634237286815 & 0.21365762713185 \tabularnewline
124 & 1 & 0.76185936169656 & 0.238140638303441 \tabularnewline
125 & 1 & 0.720261667996195 & 0.279738332003805 \tabularnewline
126 & 1 & 0.894592623761714 & 0.105407376238286 \tabularnewline
127 & 1 & 0.778300953957448 & 0.221699046042552 \tabularnewline
128 & 1 & 0.60304907398447 & 0.39695092601553 \tabularnewline
129 & 1 & 0.524556772930403 & 0.475443227069597 \tabularnewline
130 & 1 & 0.148017292596348 & 0.851982707403652 \tabularnewline
131 & 1 & 0.732336610353923 & 0.267663389646077 \tabularnewline
132 & 1 & 0.393601233406322 & 0.606398766593678 \tabularnewline
133 & 1 & 0.642153259975751 & 0.357846740024249 \tabularnewline
134 & 1 & 0.755230912420419 & 0.244769087579581 \tabularnewline
135 & 1 & 0.246786201766698 & 0.753213798233302 \tabularnewline
136 & 1 & 0.578399361492993 & 0.421600638507007 \tabularnewline
137 & 1 & 0.302950360633961 & 0.69704963936604 \tabularnewline
138 & 1 & 0.501972310500039 & 0.498027689499961 \tabularnewline
139 & 1 & 0.264773123370008 & 0.735226876629992 \tabularnewline
140 & 1 & 0.643916151965462 & 0.356083848034538 \tabularnewline
141 & 1 & 0.540506496976436 & 0.459493503023564 \tabularnewline
142 & 1 & 0.811261125247748 & 0.188738874752252 \tabularnewline
143 & 1 & 0.630025129387721 & 0.369974870612279 \tabularnewline
144 & 1 & 0.517667961688209 & 0.482332038311791 \tabularnewline
145 & 1 & 0.860917846578216 & 0.139082153421784 \tabularnewline
146 & 1 & 0.422273233809637 & 0.577726766190363 \tabularnewline
147 & 1 & 0.551888493948866 & 0.448111506051134 \tabularnewline
148 & 1 & 0.249930925673552 & 0.750069074326448 \tabularnewline
149 & 1 & 0.453871519185391 & 0.546128480814609 \tabularnewline
150 & 1 & 0.781555416555311 & 0.218444583444689 \tabularnewline
151 & 1 & 0.635484957190106 & 0.364515042809894 \tabularnewline
152 & 1 & 0.492583190709921 & 0.507416809290079 \tabularnewline
153 & 1 & 0.387055724009117 & 0.612944275990883 \tabularnewline
154 & 1 & 0.311223967659326 & 0.688776032340674 \tabularnewline
155 & 1 & 0.399441281750147 & 0.600558718249853 \tabularnewline
156 & 1 & 0.778300953957448 & 0.221699046042552 \tabularnewline
157 & 1 & 0.685136011757499 & 0.314863988242501 \tabularnewline
158 & 1 & 0.34191988237833 & 0.65808011762167 \tabularnewline
159 & 0 & 0.230507542830998 & -0.230507542830998 \tabularnewline
160 & 0 & 0.312277733229373 & -0.312277733229373 \tabularnewline
161 & 0 & 0.837676529831054 & -0.837676529831054 \tabularnewline
162 & 0 & 0.486269735310215 & -0.486269735310215 \tabularnewline
163 & 0 & 0.115794443940548 & -0.115794443940548 \tabularnewline
164 & 0 & 0.481159630055892 & -0.481159630055892 \tabularnewline
165 & 0 & 0.357449437750225 & -0.357449437750225 \tabularnewline
166 & 0 & 0.421234711859212 & -0.421234711859212 \tabularnewline
167 & 0 & 0.362874363298249 & -0.362874363298249 \tabularnewline
168 & 0 & 0.199349948263396 & -0.199349948263396 \tabularnewline
169 & 0 & 0.818660490821522 & -0.818660490821522 \tabularnewline
170 & 0 & 0.301726496478414 & -0.301726496478414 \tabularnewline
171 & 0 & 0.211681694885052 & -0.211681694885052 \tabularnewline
172 & 0 & 0.686100160754612 & -0.686100160754612 \tabularnewline
173 & 0 & 0.51132850453606 & -0.51132850453606 \tabularnewline
174 & 0 & 0.292917609249984 & -0.292917609249984 \tabularnewline
175 & 0 & 0.26016836848418 & -0.26016836848418 \tabularnewline
176 & 0 & 0.648581752657515 & -0.648581752657515 \tabularnewline
177 & 0 & 0.409016893394024 & -0.409016893394024 \tabularnewline
178 & 0 & 0.764439040599534 & -0.764439040599534 \tabularnewline
179 & 0 & 0.2295626780556 & -0.2295626780556 \tabularnewline
180 & 0 & 0.8333390502955 & -0.8333390502955 \tabularnewline
181 & 0 & 0.660982012412751 & -0.660982012412751 \tabularnewline
182 & 0 & 0.33308969095055 & -0.33308969095055 \tabularnewline
183 & 0 & 0.690270602166589 & -0.690270602166589 \tabularnewline
184 & 0 & 0.688663691775831 & -0.688663691775831 \tabularnewline
185 & 0 & 0.521748586779815 & -0.521748586779815 \tabularnewline
186 & 0 & 0.191836644901513 & -0.191836644901513 \tabularnewline
187 & 0 & 0.136194248480729 & -0.136194248480729 \tabularnewline
188 & 0 & 0.524602392095673 & -0.524602392095673 \tabularnewline
189 & 0 & 0.78155206840505 & -0.78155206840505 \tabularnewline
190 & 0 & 0.303983676057041 & -0.303983676057041 \tabularnewline
191 & 0 & 0.619821215111079 & -0.619821215111079 \tabularnewline
192 & 0 & 0.577368347017141 & -0.577368347017141 \tabularnewline
193 & 0 & 0.567644505528032 & -0.567644505528032 \tabularnewline
194 & 0 & 0.662171320139291 & -0.662171320139291 \tabularnewline
195 & 0 & 0.7345792668584 & -0.7345792668584 \tabularnewline
196 & 0 & 0.233933262717314 & -0.233933262717314 \tabularnewline
197 & 0 & 0.403065997390284 & -0.403065997390284 \tabularnewline
198 & 0 & 0.4122251242698 & -0.4122251242698 \tabularnewline
199 & 0 & 0.451977092980775 & -0.451977092980775 \tabularnewline
200 & 0 & 0.434253978823333 & -0.434253978823333 \tabularnewline
201 & 0 & 0.612868741633981 & -0.612868741633981 \tabularnewline
202 & 0 & 0.71435471734017 & -0.71435471734017 \tabularnewline
203 & 0 & 0.728441857977288 & -0.728441857977288 \tabularnewline
204 & 0 & 0.735051390345038 & -0.735051390345038 \tabularnewline
205 & 0 & 0.349958388140841 & -0.349958388140841 \tabularnewline
206 & 0 & 0.626138169229684 & -0.626138169229684 \tabularnewline
207 & 0 & 0.378952578730195 & -0.378952578730195 \tabularnewline
208 & 0 & 0.6407366409968 & -0.6407366409968 \tabularnewline
209 & 0 & 0.427029368285419 & -0.427029368285419 \tabularnewline
210 & 0 & 0.2767824032728 & -0.2767824032728 \tabularnewline
211 & 0 & 0.652175164401947 & -0.652175164401947 \tabularnewline
212 & 0 & 0.466104649043583 & -0.466104649043583 \tabularnewline
213 & 0 & 0.827627905029396 & -0.827627905029396 \tabularnewline
214 & 0 & 0.667068804508981 & -0.667068804508981 \tabularnewline
215 & 0 & 0.205189485032229 & -0.205189485032229 \tabularnewline
216 & 0 & 0.759908808874384 & -0.759908808874384 \tabularnewline
217 & 0 & 0.410864262992882 & -0.410864262992882 \tabularnewline
218 & 0 & 0.630536316687389 & -0.630536316687389 \tabularnewline
219 & 0 & 0.544325664205685 & -0.544325664205685 \tabularnewline
220 & 0 & 0.377923618593935 & -0.377923618593935 \tabularnewline
221 & 0 & 0.268679575025636 & -0.268679575025636 \tabularnewline
222 & 0 & 0.662094028530696 & -0.662094028530696 \tabularnewline
223 & 0 & 0.371883241870597 & -0.371883241870597 \tabularnewline
224 & 0 & 0.155751787278571 & -0.155751787278571 \tabularnewline
225 & 0 & 0.266892823459304 & -0.266892823459304 \tabularnewline
226 & 0 & 0.427993712263745 & -0.427993712263745 \tabularnewline
227 & 0 & 0.163126773529052 & -0.163126773529052 \tabularnewline
228 & 0 & 0.47098693992073 & -0.47098693992073 \tabularnewline
229 & 0 & 0.872383443940895 & -0.872383443940895 \tabularnewline
230 & 0 & 0.64172608259535 & -0.64172608259535 \tabularnewline
231 & 0 & 0.279385353706797 & -0.279385353706797 \tabularnewline
232 & 0 & 0.0710857865921835 & -0.0710857865921835 \tabularnewline
233 & 0 & 0.508757242070833 & -0.508757242070833 \tabularnewline
234 & 0 & 0.538738403649526 & -0.538738403649526 \tabularnewline
235 & 0 & 0.18434936939502 & -0.18434936939502 \tabularnewline
236 & 0 & 0.207136390660684 & -0.207136390660684 \tabularnewline
237 & 0 & 0.234400564859635 & -0.234400564859635 \tabularnewline
238 & 0 & 0.0883312604504473 & -0.0883312604504473 \tabularnewline
239 & 0 & 0.266718621040396 & -0.266718621040396 \tabularnewline
240 & 0 & 0.196414336996727 & -0.196414336996727 \tabularnewline
241 & 0 & 0.39832414775847 & -0.39832414775847 \tabularnewline
242 & 0 & 0.416599379008702 & -0.416599379008702 \tabularnewline
243 & 0 & 0.162821716876137 & -0.162821716876137 \tabularnewline
244 & 0 & 0.256826835994326 & -0.256826835994326 \tabularnewline
245 & 0 & 0.276914974467596 & -0.276914974467596 \tabularnewline
246 & 0 & 0.202834781054739 & -0.202834781054739 \tabularnewline
247 & 0 & 0.36727436386376 & -0.36727436386376 \tabularnewline
248 & 0 & 0.611285127777491 & -0.611285127777491 \tabularnewline
249 & 0 & 0.366494785448559 & -0.366494785448559 \tabularnewline
250 & 0 & 0.450772141845891 & -0.450772141845891 \tabularnewline
251 & 0 & 0.464237205347947 & -0.464237205347947 \tabularnewline
252 & 0 & 0.30508547572357 & -0.30508547572357 \tabularnewline
253 & 0 & 0.669676233680557 & -0.669676233680557 \tabularnewline
254 & 0 & 0.0483754807588189 & -0.0483754807588189 \tabularnewline
255 & 0 & 0.597365201257531 & -0.597365201257531 \tabularnewline
256 & 0 & 0.467786071578439 & -0.467786071578439 \tabularnewline
257 & 0 & 0.139521872571761 & -0.139521872571761 \tabularnewline
258 & 0 & 0.401715835774213 & -0.401715835774213 \tabularnewline
259 & 0 & 0.417782832003998 & -0.417782832003998 \tabularnewline
260 & 0 & 0.377142113418853 & -0.377142113418853 \tabularnewline
261 & 0 & 0.291543793843981 & -0.291543793843981 \tabularnewline
262 & 0 & 0.291172974065719 & -0.291172974065719 \tabularnewline
263 & 0 & 0.659707710572722 & -0.659707710572722 \tabularnewline
264 & 0 & 0.116211935787898 & -0.116211935787898 \tabularnewline
265 & 0 & 0.293415611144785 & -0.293415611144785 \tabularnewline
266 & 0 & 0.404195145877812 & -0.404195145877812 \tabularnewline
267 & 0 & 0.640701528938753 & -0.640701528938753 \tabularnewline
268 & 0 & 0.243678173524166 & -0.243678173524166 \tabularnewline
269 & 0 & 0.722869473919669 & -0.722869473919669 \tabularnewline
270 & 0 & 0.641491575935516 & -0.641491575935516 \tabularnewline
271 & 0 & 0.150976947102947 & -0.150976947102947 \tabularnewline
272 & 0 & 0.216279716343484 & -0.216279716343484 \tabularnewline
273 & 0 & 0.571689397840238 & -0.571689397840238 \tabularnewline
274 & 0 & 0.0666688203403835 & -0.0666688203403835 \tabularnewline
275 & 0 & 0.527554626959814 & -0.527554626959814 \tabularnewline
276 & 0 & 0.0463662623974217 & -0.0463662623974217 \tabularnewline
277 & 0 & 0.465874441957976 & -0.465874441957976 \tabularnewline
278 & 0 & 0.592464855267995 & -0.592464855267995 \tabularnewline
279 & 0 & 0.693925212798238 & -0.693925212798238 \tabularnewline
280 & 0 & 0.261074369298987 & -0.261074369298987 \tabularnewline
281 & 0 & 0.73515892394614 & -0.73515892394614 \tabularnewline
282 & 0 & 0.649383399576935 & -0.649383399576935 \tabularnewline
283 & 0 & 0.262186925042768 & -0.262186925042768 \tabularnewline
284 & 0 & 0.0546957578366119 & -0.0546957578366119 \tabularnewline
285 & 0 & 0.731290225372777 & -0.731290225372777 \tabularnewline
286 & 0 & 0.389739497085831 & -0.389739497085831 \tabularnewline
287 & 0 & 0.646034473114111 & -0.646034473114111 \tabularnewline
288 & 0 & 0.621762094593828 & -0.621762094593828 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156134&T=3

[TABLE]
[ROW][C]Fit of Logistic Regression[/C][/ROW]
[ROW][C]Index[/C][C]Actual[/C][C]Fitted[/C][C]Error[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]0.706689414076715[/C][C]0.293310585923285[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.866416508766555[/C][C]0.133583491233445[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.791041973058652[/C][C]0.208958026941348[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.299389179097086[/C][C]0.700610820902914[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.762713532824038[/C][C]0.237286467175962[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.725673950547156[/C][C]0.274326049452844[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.869903609093686[/C][C]0.130096390906314[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.761170830930137[/C][C]0.238829169069863[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.72592692293413[/C][C]0.27407307706587[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.689547742040163[/C][C]0.310452257959837[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.746609544992578[/C][C]0.253390455007422[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.88192084226783[/C][C]0.118079157732169[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.545799068095973[/C][C]0.454200931904027[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.82151778028015[/C][C]0.178482219719849[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.906855636287032[/C][C]0.0931443637129676[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.58689089643742[/C][C]0.41310910356258[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.572109348303035[/C][C]0.427890651696965[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.925408975215039[/C][C]0.0745910247849615[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.75572072468701[/C][C]0.24427927531299[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.786955198168096[/C][C]0.213044801831904[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.743523511587945[/C][C]0.256476488412055[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.604953725894298[/C][C]0.395046274105702[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.883233345269444[/C][C]0.116766654730556[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.680485248721465[/C][C]0.319514751278535[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.830475580080246[/C][C]0.169524419919754[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.718794716673827[/C][C]0.281205283326173[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.690484301143974[/C][C]0.309515698856026[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.751162510509238[/C][C]0.248837489490762[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.766974277084221[/C][C]0.233025722915779[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.377614504850309[/C][C]0.622385495149691[/C][/ROW]
[ROW][C]31[/C][C]1[/C][C]0.744708239309766[/C][C]0.255291760690234[/C][/ROW]
[ROW][C]32[/C][C]1[/C][C]0.235719371027402[/C][C]0.764280628972598[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]0.749040672665962[/C][C]0.250959327334038[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]0.774939230281182[/C][C]0.225060769718818[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]0.56858252575309[/C][C]0.43141747424691[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]0.283937075009624[/C][C]0.716062924990376[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.122576200422651[/C][C]0.877423799577349[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.632149188759943[/C][C]0.367850811240057[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.739779393071093[/C][C]0.260220606928907[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.563569508960662[/C][C]0.436430491039338[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.666936582873789[/C][C]0.333063417126211[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.738618923980915[/C][C]0.261381076019085[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]0.911769253983332[/C][C]0.0882307460166681[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]0.430146532140253[/C][C]0.569853467859747[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.694130051009549[/C][C]0.305869948990451[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]0.45169668779395[/C][C]0.54830331220605[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]0.769904106092675[/C][C]0.230095893907325[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.704297736138988[/C][C]0.295702263861012[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]0.822778975007354[/C][C]0.177221024992646[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.57840414371663[/C][C]0.42159585628337[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.8274930497011[/C][C]0.1725069502989[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]0.474736340646209[/C][C]0.525263659353791[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]0.331099546203302[/C][C]0.668900453796698[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.705325960379503[/C][C]0.294674039620497[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.114571036511044[/C][C]0.885428963488956[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.552205076837565[/C][C]0.447794923162435[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.841597198621697[/C][C]0.158402801378303[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.727041093673347[/C][C]0.272958906326653[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.534884361077593[/C][C]0.465115638922407[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.628111348966246[/C][C]0.371888651033754[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]0.121569269869355[/C][C]0.878430730130645[/C][/ROW]
[ROW][C]62[/C][C]1[/C][C]0.664516922884374[/C][C]0.335483077115626[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]0.700246049416482[/C][C]0.299753950583518[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]0.601006642451037[/C][C]0.398993357548963[/C][/ROW]
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[ROW][C]66[/C][C]1[/C][C]0.58523603008999[/C][C]0.41476396991001[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.78989748090519[/C][C]0.21010251909481[/C][/ROW]
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[ROW][C]90[/C][C]1[/C][C]0.565257186789658[/C][C]0.434742813210342[/C][/ROW]
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[ROW][C]92[/C][C]1[/C][C]0.782709066810056[/C][C]0.217290933189944[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.689242947560798[/C][C]0.310757052439202[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.524640301269035[/C][C]0.475359698730965[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.801259022280302[/C][C]0.198740977719698[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.738010217328002[/C][C]0.261989782671998[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.67380320047442[/C][C]0.326196799525581[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.784985510192991[/C][C]0.215014489807009[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.513453467136282[/C][C]0.486546532863718[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.886182401641265[/C][C]0.113817598358735[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.581045591671591[/C][C]0.418954408328409[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.93447958076435[/C][C]0.0655204192356509[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]0.431976637619919[/C][C]0.568023362380081[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.739647576978224[/C][C]0.260352423021776[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.394541749734655[/C][C]0.605458250265345[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.85831199119978[/C][C]0.14168800880022[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.761991323832865[/C][C]0.238008676167135[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.485667410460703[/C][C]0.514332589539297[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.365113566072585[/C][C]0.634886433927415[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.737325443241801[/C][C]0.262674556758199[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.667030627352857[/C][C]0.332969372647143[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.69878535826383[/C][C]0.30121464173617[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.707452279415385[/C][C]0.292547720584615[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.837499291786651[/C][C]0.162500708213349[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.685183046335104[/C][C]0.314816953664896[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.537275190595377[/C][C]0.462724809404623[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.581539818350118[/C][C]0.418460181649882[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.782802973251435[/C][C]0.217197026748565[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.391071047717513[/C][C]0.608928952282487[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.744137743005197[/C][C]0.255862256994803[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.70809482594649[/C][C]0.291905174053509[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.840806543773048[/C][C]0.159193456226952[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.78634237286815[/C][C]0.21365762713185[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.76185936169656[/C][C]0.238140638303441[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.720261667996195[/C][C]0.279738332003805[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.894592623761714[/C][C]0.105407376238286[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.778300953957448[/C][C]0.221699046042552[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.60304907398447[/C][C]0.39695092601553[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.524556772930403[/C][C]0.475443227069597[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.148017292596348[/C][C]0.851982707403652[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.732336610353923[/C][C]0.267663389646077[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.393601233406322[/C][C]0.606398766593678[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.642153259975751[/C][C]0.357846740024249[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.755230912420419[/C][C]0.244769087579581[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.246786201766698[/C][C]0.753213798233302[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.578399361492993[/C][C]0.421600638507007[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.302950360633961[/C][C]0.69704963936604[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.501972310500039[/C][C]0.498027689499961[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.264773123370008[/C][C]0.735226876629992[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.643916151965462[/C][C]0.356083848034538[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.540506496976436[/C][C]0.459493503023564[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.811261125247748[/C][C]0.188738874752252[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.630025129387721[/C][C]0.369974870612279[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.517667961688209[/C][C]0.482332038311791[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.860917846578216[/C][C]0.139082153421784[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.422273233809637[/C][C]0.577726766190363[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]0.551888493948866[/C][C]0.448111506051134[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.249930925673552[/C][C]0.750069074326448[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.453871519185391[/C][C]0.546128480814609[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.781555416555311[/C][C]0.218444583444689[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.635484957190106[/C][C]0.364515042809894[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.492583190709921[/C][C]0.507416809290079[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.387055724009117[/C][C]0.612944275990883[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.311223967659326[/C][C]0.688776032340674[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.399441281750147[/C][C]0.600558718249853[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.778300953957448[/C][C]0.221699046042552[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.685136011757499[/C][C]0.314863988242501[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.34191988237833[/C][C]0.65808011762167[/C][/ROW]
[ROW][C]159[/C][C]0[/C][C]0.230507542830998[/C][C]-0.230507542830998[/C][/ROW]
[ROW][C]160[/C][C]0[/C][C]0.312277733229373[/C][C]-0.312277733229373[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.837676529831054[/C][C]-0.837676529831054[/C][/ROW]
[ROW][C]162[/C][C]0[/C][C]0.486269735310215[/C][C]-0.486269735310215[/C][/ROW]
[ROW][C]163[/C][C]0[/C][C]0.115794443940548[/C][C]-0.115794443940548[/C][/ROW]
[ROW][C]164[/C][C]0[/C][C]0.481159630055892[/C][C]-0.481159630055892[/C][/ROW]
[ROW][C]165[/C][C]0[/C][C]0.357449437750225[/C][C]-0.357449437750225[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.421234711859212[/C][C]-0.421234711859212[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.362874363298249[/C][C]-0.362874363298249[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.199349948263396[/C][C]-0.199349948263396[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.818660490821522[/C][C]-0.818660490821522[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.301726496478414[/C][C]-0.301726496478414[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.211681694885052[/C][C]-0.211681694885052[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.686100160754612[/C][C]-0.686100160754612[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.51132850453606[/C][C]-0.51132850453606[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.292917609249984[/C][C]-0.292917609249984[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.26016836848418[/C][C]-0.26016836848418[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.648581752657515[/C][C]-0.648581752657515[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.409016893394024[/C][C]-0.409016893394024[/C][/ROW]
[ROW][C]178[/C][C]0[/C][C]0.764439040599534[/C][C]-0.764439040599534[/C][/ROW]
[ROW][C]179[/C][C]0[/C][C]0.2295626780556[/C][C]-0.2295626780556[/C][/ROW]
[ROW][C]180[/C][C]0[/C][C]0.8333390502955[/C][C]-0.8333390502955[/C][/ROW]
[ROW][C]181[/C][C]0[/C][C]0.660982012412751[/C][C]-0.660982012412751[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]0.33308969095055[/C][C]-0.33308969095055[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]0.690270602166589[/C][C]-0.690270602166589[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.688663691775831[/C][C]-0.688663691775831[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.521748586779815[/C][C]-0.521748586779815[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.191836644901513[/C][C]-0.191836644901513[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.136194248480729[/C][C]-0.136194248480729[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.524602392095673[/C][C]-0.524602392095673[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.78155206840505[/C][C]-0.78155206840505[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.303983676057041[/C][C]-0.303983676057041[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.619821215111079[/C][C]-0.619821215111079[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.577368347017141[/C][C]-0.577368347017141[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.567644505528032[/C][C]-0.567644505528032[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.662171320139291[/C][C]-0.662171320139291[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.7345792668584[/C][C]-0.7345792668584[/C][/ROW]
[ROW][C]196[/C][C]0[/C][C]0.233933262717314[/C][C]-0.233933262717314[/C][/ROW]
[ROW][C]197[/C][C]0[/C][C]0.403065997390284[/C][C]-0.403065997390284[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]0.4122251242698[/C][C]-0.4122251242698[/C][/ROW]
[ROW][C]199[/C][C]0[/C][C]0.451977092980775[/C][C]-0.451977092980775[/C][/ROW]
[ROW][C]200[/C][C]0[/C][C]0.434253978823333[/C][C]-0.434253978823333[/C][/ROW]
[ROW][C]201[/C][C]0[/C][C]0.612868741633981[/C][C]-0.612868741633981[/C][/ROW]
[ROW][C]202[/C][C]0[/C][C]0.71435471734017[/C][C]-0.71435471734017[/C][/ROW]
[ROW][C]203[/C][C]0[/C][C]0.728441857977288[/C][C]-0.728441857977288[/C][/ROW]
[ROW][C]204[/C][C]0[/C][C]0.735051390345038[/C][C]-0.735051390345038[/C][/ROW]
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[ROW][C]206[/C][C]0[/C][C]0.626138169229684[/C][C]-0.626138169229684[/C][/ROW]
[ROW][C]207[/C][C]0[/C][C]0.378952578730195[/C][C]-0.378952578730195[/C][/ROW]
[ROW][C]208[/C][C]0[/C][C]0.6407366409968[/C][C]-0.6407366409968[/C][/ROW]
[ROW][C]209[/C][C]0[/C][C]0.427029368285419[/C][C]-0.427029368285419[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]0.2767824032728[/C][C]-0.2767824032728[/C][/ROW]
[ROW][C]211[/C][C]0[/C][C]0.652175164401947[/C][C]-0.652175164401947[/C][/ROW]
[ROW][C]212[/C][C]0[/C][C]0.466104649043583[/C][C]-0.466104649043583[/C][/ROW]
[ROW][C]213[/C][C]0[/C][C]0.827627905029396[/C][C]-0.827627905029396[/C][/ROW]
[ROW][C]214[/C][C]0[/C][C]0.667068804508981[/C][C]-0.667068804508981[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]0.205189485032229[/C][C]-0.205189485032229[/C][/ROW]
[ROW][C]216[/C][C]0[/C][C]0.759908808874384[/C][C]-0.759908808874384[/C][/ROW]
[ROW][C]217[/C][C]0[/C][C]0.410864262992882[/C][C]-0.410864262992882[/C][/ROW]
[ROW][C]218[/C][C]0[/C][C]0.630536316687389[/C][C]-0.630536316687389[/C][/ROW]
[ROW][C]219[/C][C]0[/C][C]0.544325664205685[/C][C]-0.544325664205685[/C][/ROW]
[ROW][C]220[/C][C]0[/C][C]0.377923618593935[/C][C]-0.377923618593935[/C][/ROW]
[ROW][C]221[/C][C]0[/C][C]0.268679575025636[/C][C]-0.268679575025636[/C][/ROW]
[ROW][C]222[/C][C]0[/C][C]0.662094028530696[/C][C]-0.662094028530696[/C][/ROW]
[ROW][C]223[/C][C]0[/C][C]0.371883241870597[/C][C]-0.371883241870597[/C][/ROW]
[ROW][C]224[/C][C]0[/C][C]0.155751787278571[/C][C]-0.155751787278571[/C][/ROW]
[ROW][C]225[/C][C]0[/C][C]0.266892823459304[/C][C]-0.266892823459304[/C][/ROW]
[ROW][C]226[/C][C]0[/C][C]0.427993712263745[/C][C]-0.427993712263745[/C][/ROW]
[ROW][C]227[/C][C]0[/C][C]0.163126773529052[/C][C]-0.163126773529052[/C][/ROW]
[ROW][C]228[/C][C]0[/C][C]0.47098693992073[/C][C]-0.47098693992073[/C][/ROW]
[ROW][C]229[/C][C]0[/C][C]0.872383443940895[/C][C]-0.872383443940895[/C][/ROW]
[ROW][C]230[/C][C]0[/C][C]0.64172608259535[/C][C]-0.64172608259535[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]0.279385353706797[/C][C]-0.279385353706797[/C][/ROW]
[ROW][C]232[/C][C]0[/C][C]0.0710857865921835[/C][C]-0.0710857865921835[/C][/ROW]
[ROW][C]233[/C][C]0[/C][C]0.508757242070833[/C][C]-0.508757242070833[/C][/ROW]
[ROW][C]234[/C][C]0[/C][C]0.538738403649526[/C][C]-0.538738403649526[/C][/ROW]
[ROW][C]235[/C][C]0[/C][C]0.18434936939502[/C][C]-0.18434936939502[/C][/ROW]
[ROW][C]236[/C][C]0[/C][C]0.207136390660684[/C][C]-0.207136390660684[/C][/ROW]
[ROW][C]237[/C][C]0[/C][C]0.234400564859635[/C][C]-0.234400564859635[/C][/ROW]
[ROW][C]238[/C][C]0[/C][C]0.0883312604504473[/C][C]-0.0883312604504473[/C][/ROW]
[ROW][C]239[/C][C]0[/C][C]0.266718621040396[/C][C]-0.266718621040396[/C][/ROW]
[ROW][C]240[/C][C]0[/C][C]0.196414336996727[/C][C]-0.196414336996727[/C][/ROW]
[ROW][C]241[/C][C]0[/C][C]0.39832414775847[/C][C]-0.39832414775847[/C][/ROW]
[ROW][C]242[/C][C]0[/C][C]0.416599379008702[/C][C]-0.416599379008702[/C][/ROW]
[ROW][C]243[/C][C]0[/C][C]0.162821716876137[/C][C]-0.162821716876137[/C][/ROW]
[ROW][C]244[/C][C]0[/C][C]0.256826835994326[/C][C]-0.256826835994326[/C][/ROW]
[ROW][C]245[/C][C]0[/C][C]0.276914974467596[/C][C]-0.276914974467596[/C][/ROW]
[ROW][C]246[/C][C]0[/C][C]0.202834781054739[/C][C]-0.202834781054739[/C][/ROW]
[ROW][C]247[/C][C]0[/C][C]0.36727436386376[/C][C]-0.36727436386376[/C][/ROW]
[ROW][C]248[/C][C]0[/C][C]0.611285127777491[/C][C]-0.611285127777491[/C][/ROW]
[ROW][C]249[/C][C]0[/C][C]0.366494785448559[/C][C]-0.366494785448559[/C][/ROW]
[ROW][C]250[/C][C]0[/C][C]0.450772141845891[/C][C]-0.450772141845891[/C][/ROW]
[ROW][C]251[/C][C]0[/C][C]0.464237205347947[/C][C]-0.464237205347947[/C][/ROW]
[ROW][C]252[/C][C]0[/C][C]0.30508547572357[/C][C]-0.30508547572357[/C][/ROW]
[ROW][C]253[/C][C]0[/C][C]0.669676233680557[/C][C]-0.669676233680557[/C][/ROW]
[ROW][C]254[/C][C]0[/C][C]0.0483754807588189[/C][C]-0.0483754807588189[/C][/ROW]
[ROW][C]255[/C][C]0[/C][C]0.597365201257531[/C][C]-0.597365201257531[/C][/ROW]
[ROW][C]256[/C][C]0[/C][C]0.467786071578439[/C][C]-0.467786071578439[/C][/ROW]
[ROW][C]257[/C][C]0[/C][C]0.139521872571761[/C][C]-0.139521872571761[/C][/ROW]
[ROW][C]258[/C][C]0[/C][C]0.401715835774213[/C][C]-0.401715835774213[/C][/ROW]
[ROW][C]259[/C][C]0[/C][C]0.417782832003998[/C][C]-0.417782832003998[/C][/ROW]
[ROW][C]260[/C][C]0[/C][C]0.377142113418853[/C][C]-0.377142113418853[/C][/ROW]
[ROW][C]261[/C][C]0[/C][C]0.291543793843981[/C][C]-0.291543793843981[/C][/ROW]
[ROW][C]262[/C][C]0[/C][C]0.291172974065719[/C][C]-0.291172974065719[/C][/ROW]
[ROW][C]263[/C][C]0[/C][C]0.659707710572722[/C][C]-0.659707710572722[/C][/ROW]
[ROW][C]264[/C][C]0[/C][C]0.116211935787898[/C][C]-0.116211935787898[/C][/ROW]
[ROW][C]265[/C][C]0[/C][C]0.293415611144785[/C][C]-0.293415611144785[/C][/ROW]
[ROW][C]266[/C][C]0[/C][C]0.404195145877812[/C][C]-0.404195145877812[/C][/ROW]
[ROW][C]267[/C][C]0[/C][C]0.640701528938753[/C][C]-0.640701528938753[/C][/ROW]
[ROW][C]268[/C][C]0[/C][C]0.243678173524166[/C][C]-0.243678173524166[/C][/ROW]
[ROW][C]269[/C][C]0[/C][C]0.722869473919669[/C][C]-0.722869473919669[/C][/ROW]
[ROW][C]270[/C][C]0[/C][C]0.641491575935516[/C][C]-0.641491575935516[/C][/ROW]
[ROW][C]271[/C][C]0[/C][C]0.150976947102947[/C][C]-0.150976947102947[/C][/ROW]
[ROW][C]272[/C][C]0[/C][C]0.216279716343484[/C][C]-0.216279716343484[/C][/ROW]
[ROW][C]273[/C][C]0[/C][C]0.571689397840238[/C][C]-0.571689397840238[/C][/ROW]
[ROW][C]274[/C][C]0[/C][C]0.0666688203403835[/C][C]-0.0666688203403835[/C][/ROW]
[ROW][C]275[/C][C]0[/C][C]0.527554626959814[/C][C]-0.527554626959814[/C][/ROW]
[ROW][C]276[/C][C]0[/C][C]0.0463662623974217[/C][C]-0.0463662623974217[/C][/ROW]
[ROW][C]277[/C][C]0[/C][C]0.465874441957976[/C][C]-0.465874441957976[/C][/ROW]
[ROW][C]278[/C][C]0[/C][C]0.592464855267995[/C][C]-0.592464855267995[/C][/ROW]
[ROW][C]279[/C][C]0[/C][C]0.693925212798238[/C][C]-0.693925212798238[/C][/ROW]
[ROW][C]280[/C][C]0[/C][C]0.261074369298987[/C][C]-0.261074369298987[/C][/ROW]
[ROW][C]281[/C][C]0[/C][C]0.73515892394614[/C][C]-0.73515892394614[/C][/ROW]
[ROW][C]282[/C][C]0[/C][C]0.649383399576935[/C][C]-0.649383399576935[/C][/ROW]
[ROW][C]283[/C][C]0[/C][C]0.262186925042768[/C][C]-0.262186925042768[/C][/ROW]
[ROW][C]284[/C][C]0[/C][C]0.0546957578366119[/C][C]-0.0546957578366119[/C][/ROW]
[ROW][C]285[/C][C]0[/C][C]0.731290225372777[/C][C]-0.731290225372777[/C][/ROW]
[ROW][C]286[/C][C]0[/C][C]0.389739497085831[/C][C]-0.389739497085831[/C][/ROW]
[ROW][C]287[/C][C]0[/C][C]0.646034473114111[/C][C]-0.646034473114111[/C][/ROW]
[ROW][C]288[/C][C]0[/C][C]0.621762094593828[/C][C]-0.621762094593828[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156134&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156134&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Fit of Logistic Regression
IndexActualFittedError
110.7066894140767150.293310585923285
210.8664165087665550.133583491233445
310.7910419730586520.208958026941348
410.2993891790970860.700610820902914
510.7627135328240380.237286467175962
610.7256739505471560.274326049452844
710.8699036090936860.130096390906314
810.7611708309301370.238829169069863
910.725926922934130.27407307706587
1010.6895477420401630.310452257959837
1110.7466095449925780.253390455007422
1210.881920842267830.118079157732169
1310.5457990680959730.454200931904027
1410.821517780280150.178482219719849
1510.9068556362870320.0931443637129676
1610.586890896437420.41310910356258
1710.5721093483030350.427890651696965
1810.9254089752150390.0745910247849615
1910.755720724687010.24427927531299
2010.7869551981680960.213044801831904
2110.7435235115879450.256476488412055
2210.6049537258942980.395046274105702
2310.8832333452694440.116766654730556
2410.6804852487214650.319514751278535
2510.8304755800802460.169524419919754
2610.7187947166738270.281205283326173
2710.6904843011439740.309515698856026
2810.7511625105092380.248837489490762
2910.7669742770842210.233025722915779
3010.3776145048503090.622385495149691
3110.7447082393097660.255291760690234
3210.2357193710274020.764280628972598
3310.7490406726659620.250959327334038
3410.7749392302811820.225060769718818
3510.568582525753090.43141747424691
3610.2839370750096240.716062924990376
3710.1225762004226510.877423799577349
3810.6321491887599430.367850811240057
3910.7397793930710930.260220606928907
4010.5635695089606620.436430491039338
4110.6669365828737890.333063417126211
4210.7386189239809150.261381076019085
4310.9117692539833320.0882307460166681
4410.4301465321402530.569853467859747
4510.6941300510095490.305869948990451
4610.451696687793950.54830331220605
4710.7699041060926750.230095893907325
4810.7042977361389880.295702263861012
4910.8227789750073540.177221024992646
5010.578404143716630.42159585628337
5110.82749304970110.1725069502989
5210.4747363406462090.525263659353791
5310.3310995462033020.668900453796698
5410.7053259603795030.294674039620497
5510.1145710365110440.885428963488956
5610.5522050768375650.447794923162435
5710.8415971986216970.158402801378303
5810.7270410936733470.272958906326653
5910.5348843610775930.465115638922407
6010.6281113489662460.371888651033754
6110.1215692698693550.878430730130645
6210.6645169228843740.335483077115626
6310.7002460494164820.299753950583518
6410.6010066424510370.398993357548963
6510.7768541849903760.223145815009624
6610.585236030089990.41476396991001
6710.789897480905190.21010251909481
6810.5855314674472150.414468532552785
6910.6794615048750140.320538495124986
7010.7011098201831580.298890179816842
7110.3075456283530250.692454371646975
7210.6761459670204680.323854032979532
7310.8671492440970510.132850755902949
7410.8383284618799480.161671538120052
7510.6192887083844920.380711291615508
7610.6879570501666410.312042949833359
7710.8655164667980240.134483533201976
7810.685531842316130.31446815768387
7910.4850138844502570.514986115549743
8010.6556312821548180.344368717845182
8110.6790741558104270.320925844189573
8210.7839551777521870.216044822247813
8310.7201785723475050.279821427652495
8410.6932582324669880.306741767533012
8510.6806340851323260.319365914867674
8610.556477291763690.44352270823631
8710.7356515025399420.264348497460058
8810.6573194306837320.342680569316268
8910.4201863941039020.579813605896098
9010.5652571867896580.434742813210342
9110.8337529383420830.166247061657917
9210.7827090668100560.217290933189944
9310.6892429475607980.310757052439202
9410.5246403012690350.475359698730965
9510.8012590222803020.198740977719698
9610.7380102173280020.261989782671998
9710.673803200474420.326196799525581
9810.7849855101929910.215014489807009
9910.5134534671362820.486546532863718
10010.8861824016412650.113817598358735
10110.5810455916715910.418954408328409
10210.934479580764350.0655204192356509
10310.4319766376199190.568023362380081
10410.7396475769782240.260352423021776
10510.3945417497346550.605458250265345
10610.858311991199780.14168800880022
10710.7619913238328650.238008676167135
10810.4856674104607030.514332589539297
10910.3651135660725850.634886433927415
11010.7373254432418010.262674556758199
11110.6670306273528570.332969372647143
11210.698785358263830.30121464173617
11310.7074522794153850.292547720584615
11410.8374992917866510.162500708213349
11510.6851830463351040.314816953664896
11610.5372751905953770.462724809404623
11710.5815398183501180.418460181649882
11810.7828029732514350.217197026748565
11910.3910710477175130.608928952282487
12010.7441377430051970.255862256994803
12110.708094825946490.291905174053509
12210.8408065437730480.159193456226952
12310.786342372868150.21365762713185
12410.761859361696560.238140638303441
12510.7202616679961950.279738332003805
12610.8945926237617140.105407376238286
12710.7783009539574480.221699046042552
12810.603049073984470.39695092601553
12910.5245567729304030.475443227069597
13010.1480172925963480.851982707403652
13110.7323366103539230.267663389646077
13210.3936012334063220.606398766593678
13310.6421532599757510.357846740024249
13410.7552309124204190.244769087579581
13510.2467862017666980.753213798233302
13610.5783993614929930.421600638507007
13710.3029503606339610.69704963936604
13810.5019723105000390.498027689499961
13910.2647731233700080.735226876629992
14010.6439161519654620.356083848034538
14110.5405064969764360.459493503023564
14210.8112611252477480.188738874752252
14310.6300251293877210.369974870612279
14410.5176679616882090.482332038311791
14510.8609178465782160.139082153421784
14610.4222732338096370.577726766190363
14710.5518884939488660.448111506051134
14810.2499309256735520.750069074326448
14910.4538715191853910.546128480814609
15010.7815554165553110.218444583444689
15110.6354849571901060.364515042809894
15210.4925831907099210.507416809290079
15310.3870557240091170.612944275990883
15410.3112239676593260.688776032340674
15510.3994412817501470.600558718249853
15610.7783009539574480.221699046042552
15710.6851360117574990.314863988242501
15810.341919882378330.65808011762167
15900.230507542830998-0.230507542830998
16000.312277733229373-0.312277733229373
16100.837676529831054-0.837676529831054
16200.486269735310215-0.486269735310215
16300.115794443940548-0.115794443940548
16400.481159630055892-0.481159630055892
16500.357449437750225-0.357449437750225
16600.421234711859212-0.421234711859212
16700.362874363298249-0.362874363298249
16800.199349948263396-0.199349948263396
16900.818660490821522-0.818660490821522
17000.301726496478414-0.301726496478414
17100.211681694885052-0.211681694885052
17200.686100160754612-0.686100160754612
17300.51132850453606-0.51132850453606
17400.292917609249984-0.292917609249984
17500.26016836848418-0.26016836848418
17600.648581752657515-0.648581752657515
17700.409016893394024-0.409016893394024
17800.764439040599534-0.764439040599534
17900.2295626780556-0.2295626780556
18000.8333390502955-0.8333390502955
18100.660982012412751-0.660982012412751
18200.33308969095055-0.33308969095055
18300.690270602166589-0.690270602166589
18400.688663691775831-0.688663691775831
18500.521748586779815-0.521748586779815
18600.191836644901513-0.191836644901513
18700.136194248480729-0.136194248480729
18800.524602392095673-0.524602392095673
18900.78155206840505-0.78155206840505
19000.303983676057041-0.303983676057041
19100.619821215111079-0.619821215111079
19200.577368347017141-0.577368347017141
19300.567644505528032-0.567644505528032
19400.662171320139291-0.662171320139291
19500.7345792668584-0.7345792668584
19600.233933262717314-0.233933262717314
19700.403065997390284-0.403065997390284
19800.4122251242698-0.4122251242698
19900.451977092980775-0.451977092980775
20000.434253978823333-0.434253978823333
20100.612868741633981-0.612868741633981
20200.71435471734017-0.71435471734017
20300.728441857977288-0.728441857977288
20400.735051390345038-0.735051390345038
20500.349958388140841-0.349958388140841
20600.626138169229684-0.626138169229684
20700.378952578730195-0.378952578730195
20800.6407366409968-0.6407366409968
20900.427029368285419-0.427029368285419
21000.2767824032728-0.2767824032728
21100.652175164401947-0.652175164401947
21200.466104649043583-0.466104649043583
21300.827627905029396-0.827627905029396
21400.667068804508981-0.667068804508981
21500.205189485032229-0.205189485032229
21600.759908808874384-0.759908808874384
21700.410864262992882-0.410864262992882
21800.630536316687389-0.630536316687389
21900.544325664205685-0.544325664205685
22000.377923618593935-0.377923618593935
22100.268679575025636-0.268679575025636
22200.662094028530696-0.662094028530696
22300.371883241870597-0.371883241870597
22400.155751787278571-0.155751787278571
22500.266892823459304-0.266892823459304
22600.427993712263745-0.427993712263745
22700.163126773529052-0.163126773529052
22800.47098693992073-0.47098693992073
22900.872383443940895-0.872383443940895
23000.64172608259535-0.64172608259535
23100.279385353706797-0.279385353706797
23200.0710857865921835-0.0710857865921835
23300.508757242070833-0.508757242070833
23400.538738403649526-0.538738403649526
23500.18434936939502-0.18434936939502
23600.207136390660684-0.207136390660684
23700.234400564859635-0.234400564859635
23800.0883312604504473-0.0883312604504473
23900.266718621040396-0.266718621040396
24000.196414336996727-0.196414336996727
24100.39832414775847-0.39832414775847
24200.416599379008702-0.416599379008702
24300.162821716876137-0.162821716876137
24400.256826835994326-0.256826835994326
24500.276914974467596-0.276914974467596
24600.202834781054739-0.202834781054739
24700.36727436386376-0.36727436386376
24800.611285127777491-0.611285127777491
24900.366494785448559-0.366494785448559
25000.450772141845891-0.450772141845891
25100.464237205347947-0.464237205347947
25200.30508547572357-0.30508547572357
25300.669676233680557-0.669676233680557
25400.0483754807588189-0.0483754807588189
25500.597365201257531-0.597365201257531
25600.467786071578439-0.467786071578439
25700.139521872571761-0.139521872571761
25800.401715835774213-0.401715835774213
25900.417782832003998-0.417782832003998
26000.377142113418853-0.377142113418853
26100.291543793843981-0.291543793843981
26200.291172974065719-0.291172974065719
26300.659707710572722-0.659707710572722
26400.116211935787898-0.116211935787898
26500.293415611144785-0.293415611144785
26600.404195145877812-0.404195145877812
26700.640701528938753-0.640701528938753
26800.243678173524166-0.243678173524166
26900.722869473919669-0.722869473919669
27000.641491575935516-0.641491575935516
27100.150976947102947-0.150976947102947
27200.216279716343484-0.216279716343484
27300.571689397840238-0.571689397840238
27400.0666688203403835-0.0666688203403835
27500.527554626959814-0.527554626959814
27600.0463662623974217-0.0463662623974217
27700.465874441957976-0.465874441957976
27800.592464855267995-0.592464855267995
27900.693925212798238-0.693925212798238
28000.261074369298987-0.261074369298987
28100.73515892394614-0.73515892394614
28200.649383399576935-0.649383399576935
28300.262186925042768-0.262186925042768
28400.0546957578366119-0.0546957578366119
28500.731290225372777-0.731290225372777
28600.389739497085831-0.389739497085831
28700.646034473114111-0.646034473114111
28800.621762094593828-0.621762094593828






Type I & II errors for various threshold values
ThresholdType IType II
0.0101
0.0201
0.0301
0.0401
0.0500.984615384615385
0.0600.976923076923077
0.0700.96923076923077
0.0800.961538461538462
0.0900.953846153846154
0.100.953846153846154
0.1100.953846153846154
0.120.006329113924050630.938461538461538
0.130.01898734177215190.938461538461538
0.140.01898734177215190.923076923076923
0.150.02531645569620250.923076923076923
0.160.02531645569620250.907692307692308
0.170.02531645569620250.892307692307692
0.180.02531645569620250.892307692307692
0.190.02531645569620250.884615384615385
0.20.02531645569620250.861538461538462
0.210.02531645569620250.838461538461538
0.220.02531645569620250.823076923076923
0.230.02531645569620250.815384615384615
0.240.03164556962025320.792307692307692
0.250.04430379746835440.784615384615385
0.260.04430379746835440.776923076923077
0.270.05063291139240510.730769230769231
0.280.05063291139240510.707692307692308
0.290.05696202531645570.707692307692308
0.30.06329113924050630.676923076923077
0.310.07594936708860760.653846153846154
0.320.08227848101265820.646153846153846
0.330.08227848101265820.646153846153846
0.340.08860759493670890.638461538461538
0.350.09493670886075950.63076923076923
0.360.09493670886075950.623076923076923
0.370.101265822784810.6
0.380.1075949367088610.569230769230769
0.390.1139240506329110.561538461538462
0.40.1392405063291140.553846153846154
0.410.1392405063291140.523076923076923
0.420.1392405063291140.492307692307692
0.430.1518987341772150.469230769230769
0.440.1645569620253160.461538461538462
0.450.1645569620253160.461538461538462
0.460.1772151898734180.446153846153846
0.470.1772151898734180.415384615384615
0.480.1835443037974680.407692307692308
0.490.196202531645570.392307692307692
0.50.202531645569620.392307692307692
0.510.2088607594936710.384615384615385
0.520.2215189873417720.376923076923077
0.530.2341772151898730.353846153846154
0.540.2468354430379750.346153846153846
0.550.2594936708860760.338461538461538
0.560.2784810126582280.338461538461538
0.570.297468354430380.330769230769231
0.580.3164556962025320.315384615384615
0.590.3481012658227850.315384615384615
0.60.3481012658227850.3
0.610.3670886075949370.3
0.620.3734177215189870.276923076923077
0.630.3797468354430380.261538461538462
0.640.398734177215190.253846153846154
0.650.4113924050632910.2
0.660.4240506329113920.184615384615385
0.670.4430379746835440.146153846153846
0.680.4683544303797470.146153846153846
0.690.5189873417721520.130769230769231
0.70.5443037974683540.115384615384615
0.710.5886075949367090.115384615384615
0.720.594936708860760.107692307692308
0.730.6265822784810130.0923076923076923
0.740.6708860759493670.0615384615384615
0.750.702531645569620.0615384615384615
0.760.7215189873417720.0538461538461538
0.770.7594936708860760.0461538461538462
0.780.7848101265822780.0461538461538462
0.790.8354430379746840.0384615384615385
0.80.8417721518987340.0384615384615385
0.810.8481012658227850.0384615384615385
0.820.8544303797468350.0307692307692308
0.830.8734177215189870.0230769230769231
0.840.898734177215190.00769230769230769
0.850.911392405063290.00769230769230769
0.860.9177215189873420.00769230769230769
0.870.9493670886075950.00769230769230769
0.880.9493670886075950
0.890.9683544303797470
0.90.9746835443037970
0.910.9810126582278480
0.920.9873417721518990
0.930.993670886075950
0.9410
0.9510
0.9610
0.9710
0.9810
0.9910

\begin{tabular}{lllllllll}
\hline
Type I & II errors for various threshold values \tabularnewline
Threshold & Type I & Type II \tabularnewline
0.01 & 0 & 1 \tabularnewline
0.02 & 0 & 1 \tabularnewline
0.03 & 0 & 1 \tabularnewline
0.04 & 0 & 1 \tabularnewline
0.05 & 0 & 0.984615384615385 \tabularnewline
0.06 & 0 & 0.976923076923077 \tabularnewline
0.07 & 0 & 0.96923076923077 \tabularnewline
0.08 & 0 & 0.961538461538462 \tabularnewline
0.09 & 0 & 0.953846153846154 \tabularnewline
0.1 & 0 & 0.953846153846154 \tabularnewline
0.11 & 0 & 0.953846153846154 \tabularnewline
0.12 & 0.00632911392405063 & 0.938461538461538 \tabularnewline
0.13 & 0.0189873417721519 & 0.938461538461538 \tabularnewline
0.14 & 0.0189873417721519 & 0.923076923076923 \tabularnewline
0.15 & 0.0253164556962025 & 0.923076923076923 \tabularnewline
0.16 & 0.0253164556962025 & 0.907692307692308 \tabularnewline
0.17 & 0.0253164556962025 & 0.892307692307692 \tabularnewline
0.18 & 0.0253164556962025 & 0.892307692307692 \tabularnewline
0.19 & 0.0253164556962025 & 0.884615384615385 \tabularnewline
0.2 & 0.0253164556962025 & 0.861538461538462 \tabularnewline
0.21 & 0.0253164556962025 & 0.838461538461538 \tabularnewline
0.22 & 0.0253164556962025 & 0.823076923076923 \tabularnewline
0.23 & 0.0253164556962025 & 0.815384615384615 \tabularnewline
0.24 & 0.0316455696202532 & 0.792307692307692 \tabularnewline
0.25 & 0.0443037974683544 & 0.784615384615385 \tabularnewline
0.26 & 0.0443037974683544 & 0.776923076923077 \tabularnewline
0.27 & 0.0506329113924051 & 0.730769230769231 \tabularnewline
0.28 & 0.0506329113924051 & 0.707692307692308 \tabularnewline
0.29 & 0.0569620253164557 & 0.707692307692308 \tabularnewline
0.3 & 0.0632911392405063 & 0.676923076923077 \tabularnewline
0.31 & 0.0759493670886076 & 0.653846153846154 \tabularnewline
0.32 & 0.0822784810126582 & 0.646153846153846 \tabularnewline
0.33 & 0.0822784810126582 & 0.646153846153846 \tabularnewline
0.34 & 0.0886075949367089 & 0.638461538461538 \tabularnewline
0.35 & 0.0949367088607595 & 0.63076923076923 \tabularnewline
0.36 & 0.0949367088607595 & 0.623076923076923 \tabularnewline
0.37 & 0.10126582278481 & 0.6 \tabularnewline
0.38 & 0.107594936708861 & 0.569230769230769 \tabularnewline
0.39 & 0.113924050632911 & 0.561538461538462 \tabularnewline
0.4 & 0.139240506329114 & 0.553846153846154 \tabularnewline
0.41 & 0.139240506329114 & 0.523076923076923 \tabularnewline
0.42 & 0.139240506329114 & 0.492307692307692 \tabularnewline
0.43 & 0.151898734177215 & 0.469230769230769 \tabularnewline
0.44 & 0.164556962025316 & 0.461538461538462 \tabularnewline
0.45 & 0.164556962025316 & 0.461538461538462 \tabularnewline
0.46 & 0.177215189873418 & 0.446153846153846 \tabularnewline
0.47 & 0.177215189873418 & 0.415384615384615 \tabularnewline
0.48 & 0.183544303797468 & 0.407692307692308 \tabularnewline
0.49 & 0.19620253164557 & 0.392307692307692 \tabularnewline
0.5 & 0.20253164556962 & 0.392307692307692 \tabularnewline
0.51 & 0.208860759493671 & 0.384615384615385 \tabularnewline
0.52 & 0.221518987341772 & 0.376923076923077 \tabularnewline
0.53 & 0.234177215189873 & 0.353846153846154 \tabularnewline
0.54 & 0.246835443037975 & 0.346153846153846 \tabularnewline
0.55 & 0.259493670886076 & 0.338461538461538 \tabularnewline
0.56 & 0.278481012658228 & 0.338461538461538 \tabularnewline
0.57 & 0.29746835443038 & 0.330769230769231 \tabularnewline
0.58 & 0.316455696202532 & 0.315384615384615 \tabularnewline
0.59 & 0.348101265822785 & 0.315384615384615 \tabularnewline
0.6 & 0.348101265822785 & 0.3 \tabularnewline
0.61 & 0.367088607594937 & 0.3 \tabularnewline
0.62 & 0.373417721518987 & 0.276923076923077 \tabularnewline
0.63 & 0.379746835443038 & 0.261538461538462 \tabularnewline
0.64 & 0.39873417721519 & 0.253846153846154 \tabularnewline
0.65 & 0.411392405063291 & 0.2 \tabularnewline
0.66 & 0.424050632911392 & 0.184615384615385 \tabularnewline
0.67 & 0.443037974683544 & 0.146153846153846 \tabularnewline
0.68 & 0.468354430379747 & 0.146153846153846 \tabularnewline
0.69 & 0.518987341772152 & 0.130769230769231 \tabularnewline
0.7 & 0.544303797468354 & 0.115384615384615 \tabularnewline
0.71 & 0.588607594936709 & 0.115384615384615 \tabularnewline
0.72 & 0.59493670886076 & 0.107692307692308 \tabularnewline
0.73 & 0.626582278481013 & 0.0923076923076923 \tabularnewline
0.74 & 0.670886075949367 & 0.0615384615384615 \tabularnewline
0.75 & 0.70253164556962 & 0.0615384615384615 \tabularnewline
0.76 & 0.721518987341772 & 0.0538461538461538 \tabularnewline
0.77 & 0.759493670886076 & 0.0461538461538462 \tabularnewline
0.78 & 0.784810126582278 & 0.0461538461538462 \tabularnewline
0.79 & 0.835443037974684 & 0.0384615384615385 \tabularnewline
0.8 & 0.841772151898734 & 0.0384615384615385 \tabularnewline
0.81 & 0.848101265822785 & 0.0384615384615385 \tabularnewline
0.82 & 0.854430379746835 & 0.0307692307692308 \tabularnewline
0.83 & 0.873417721518987 & 0.0230769230769231 \tabularnewline
0.84 & 0.89873417721519 & 0.00769230769230769 \tabularnewline
0.85 & 0.91139240506329 & 0.00769230769230769 \tabularnewline
0.86 & 0.917721518987342 & 0.00769230769230769 \tabularnewline
0.87 & 0.949367088607595 & 0.00769230769230769 \tabularnewline
0.88 & 0.949367088607595 & 0 \tabularnewline
0.89 & 0.968354430379747 & 0 \tabularnewline
0.9 & 0.974683544303797 & 0 \tabularnewline
0.91 & 0.981012658227848 & 0 \tabularnewline
0.92 & 0.987341772151899 & 0 \tabularnewline
0.93 & 0.99367088607595 & 0 \tabularnewline
0.94 & 1 & 0 \tabularnewline
0.95 & 1 & 0 \tabularnewline
0.96 & 1 & 0 \tabularnewline
0.97 & 1 & 0 \tabularnewline
0.98 & 1 & 0 \tabularnewline
0.99 & 1 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156134&T=4

[TABLE]
[ROW][C]Type I & II errors for various threshold values[/C][/ROW]
[ROW][C]Threshold[/C][C]Type I[/C][C]Type II[/C][/ROW]
[ROW][C]0.01[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]0.02[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]0.03[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]0.05[/C][C]0[/C][C]0.984615384615385[/C][/ROW]
[ROW][C]0.06[/C][C]0[/C][C]0.976923076923077[/C][/ROW]
[ROW][C]0.07[/C][C]0[/C][C]0.96923076923077[/C][/ROW]
[ROW][C]0.08[/C][C]0[/C][C]0.961538461538462[/C][/ROW]
[ROW][C]0.09[/C][C]0[/C][C]0.953846153846154[/C][/ROW]
[ROW][C]0.1[/C][C]0[/C][C]0.953846153846154[/C][/ROW]
[ROW][C]0.11[/C][C]0[/C][C]0.953846153846154[/C][/ROW]
[ROW][C]0.12[/C][C]0.00632911392405063[/C][C]0.938461538461538[/C][/ROW]
[ROW][C]0.13[/C][C]0.0189873417721519[/C][C]0.938461538461538[/C][/ROW]
[ROW][C]0.14[/C][C]0.0189873417721519[/C][C]0.923076923076923[/C][/ROW]
[ROW][C]0.15[/C][C]0.0253164556962025[/C][C]0.923076923076923[/C][/ROW]
[ROW][C]0.16[/C][C]0.0253164556962025[/C][C]0.907692307692308[/C][/ROW]
[ROW][C]0.17[/C][C]0.0253164556962025[/C][C]0.892307692307692[/C][/ROW]
[ROW][C]0.18[/C][C]0.0253164556962025[/C][C]0.892307692307692[/C][/ROW]
[ROW][C]0.19[/C][C]0.0253164556962025[/C][C]0.884615384615385[/C][/ROW]
[ROW][C]0.2[/C][C]0.0253164556962025[/C][C]0.861538461538462[/C][/ROW]
[ROW][C]0.21[/C][C]0.0253164556962025[/C][C]0.838461538461538[/C][/ROW]
[ROW][C]0.22[/C][C]0.0253164556962025[/C][C]0.823076923076923[/C][/ROW]
[ROW][C]0.23[/C][C]0.0253164556962025[/C][C]0.815384615384615[/C][/ROW]
[ROW][C]0.24[/C][C]0.0316455696202532[/C][C]0.792307692307692[/C][/ROW]
[ROW][C]0.25[/C][C]0.0443037974683544[/C][C]0.784615384615385[/C][/ROW]
[ROW][C]0.26[/C][C]0.0443037974683544[/C][C]0.776923076923077[/C][/ROW]
[ROW][C]0.27[/C][C]0.0506329113924051[/C][C]0.730769230769231[/C][/ROW]
[ROW][C]0.28[/C][C]0.0506329113924051[/C][C]0.707692307692308[/C][/ROW]
[ROW][C]0.29[/C][C]0.0569620253164557[/C][C]0.707692307692308[/C][/ROW]
[ROW][C]0.3[/C][C]0.0632911392405063[/C][C]0.676923076923077[/C][/ROW]
[ROW][C]0.31[/C][C]0.0759493670886076[/C][C]0.653846153846154[/C][/ROW]
[ROW][C]0.32[/C][C]0.0822784810126582[/C][C]0.646153846153846[/C][/ROW]
[ROW][C]0.33[/C][C]0.0822784810126582[/C][C]0.646153846153846[/C][/ROW]
[ROW][C]0.34[/C][C]0.0886075949367089[/C][C]0.638461538461538[/C][/ROW]
[ROW][C]0.35[/C][C]0.0949367088607595[/C][C]0.63076923076923[/C][/ROW]
[ROW][C]0.36[/C][C]0.0949367088607595[/C][C]0.623076923076923[/C][/ROW]
[ROW][C]0.37[/C][C]0.10126582278481[/C][C]0.6[/C][/ROW]
[ROW][C]0.38[/C][C]0.107594936708861[/C][C]0.569230769230769[/C][/ROW]
[ROW][C]0.39[/C][C]0.113924050632911[/C][C]0.561538461538462[/C][/ROW]
[ROW][C]0.4[/C][C]0.139240506329114[/C][C]0.553846153846154[/C][/ROW]
[ROW][C]0.41[/C][C]0.139240506329114[/C][C]0.523076923076923[/C][/ROW]
[ROW][C]0.42[/C][C]0.139240506329114[/C][C]0.492307692307692[/C][/ROW]
[ROW][C]0.43[/C][C]0.151898734177215[/C][C]0.469230769230769[/C][/ROW]
[ROW][C]0.44[/C][C]0.164556962025316[/C][C]0.461538461538462[/C][/ROW]
[ROW][C]0.45[/C][C]0.164556962025316[/C][C]0.461538461538462[/C][/ROW]
[ROW][C]0.46[/C][C]0.177215189873418[/C][C]0.446153846153846[/C][/ROW]
[ROW][C]0.47[/C][C]0.177215189873418[/C][C]0.415384615384615[/C][/ROW]
[ROW][C]0.48[/C][C]0.183544303797468[/C][C]0.407692307692308[/C][/ROW]
[ROW][C]0.49[/C][C]0.19620253164557[/C][C]0.392307692307692[/C][/ROW]
[ROW][C]0.5[/C][C]0.20253164556962[/C][C]0.392307692307692[/C][/ROW]
[ROW][C]0.51[/C][C]0.208860759493671[/C][C]0.384615384615385[/C][/ROW]
[ROW][C]0.52[/C][C]0.221518987341772[/C][C]0.376923076923077[/C][/ROW]
[ROW][C]0.53[/C][C]0.234177215189873[/C][C]0.353846153846154[/C][/ROW]
[ROW][C]0.54[/C][C]0.246835443037975[/C][C]0.346153846153846[/C][/ROW]
[ROW][C]0.55[/C][C]0.259493670886076[/C][C]0.338461538461538[/C][/ROW]
[ROW][C]0.56[/C][C]0.278481012658228[/C][C]0.338461538461538[/C][/ROW]
[ROW][C]0.57[/C][C]0.29746835443038[/C][C]0.330769230769231[/C][/ROW]
[ROW][C]0.58[/C][C]0.316455696202532[/C][C]0.315384615384615[/C][/ROW]
[ROW][C]0.59[/C][C]0.348101265822785[/C][C]0.315384615384615[/C][/ROW]
[ROW][C]0.6[/C][C]0.348101265822785[/C][C]0.3[/C][/ROW]
[ROW][C]0.61[/C][C]0.367088607594937[/C][C]0.3[/C][/ROW]
[ROW][C]0.62[/C][C]0.373417721518987[/C][C]0.276923076923077[/C][/ROW]
[ROW][C]0.63[/C][C]0.379746835443038[/C][C]0.261538461538462[/C][/ROW]
[ROW][C]0.64[/C][C]0.39873417721519[/C][C]0.253846153846154[/C][/ROW]
[ROW][C]0.65[/C][C]0.411392405063291[/C][C]0.2[/C][/ROW]
[ROW][C]0.66[/C][C]0.424050632911392[/C][C]0.184615384615385[/C][/ROW]
[ROW][C]0.67[/C][C]0.443037974683544[/C][C]0.146153846153846[/C][/ROW]
[ROW][C]0.68[/C][C]0.468354430379747[/C][C]0.146153846153846[/C][/ROW]
[ROW][C]0.69[/C][C]0.518987341772152[/C][C]0.130769230769231[/C][/ROW]
[ROW][C]0.7[/C][C]0.544303797468354[/C][C]0.115384615384615[/C][/ROW]
[ROW][C]0.71[/C][C]0.588607594936709[/C][C]0.115384615384615[/C][/ROW]
[ROW][C]0.72[/C][C]0.59493670886076[/C][C]0.107692307692308[/C][/ROW]
[ROW][C]0.73[/C][C]0.626582278481013[/C][C]0.0923076923076923[/C][/ROW]
[ROW][C]0.74[/C][C]0.670886075949367[/C][C]0.0615384615384615[/C][/ROW]
[ROW][C]0.75[/C][C]0.70253164556962[/C][C]0.0615384615384615[/C][/ROW]
[ROW][C]0.76[/C][C]0.721518987341772[/C][C]0.0538461538461538[/C][/ROW]
[ROW][C]0.77[/C][C]0.759493670886076[/C][C]0.0461538461538462[/C][/ROW]
[ROW][C]0.78[/C][C]0.784810126582278[/C][C]0.0461538461538462[/C][/ROW]
[ROW][C]0.79[/C][C]0.835443037974684[/C][C]0.0384615384615385[/C][/ROW]
[ROW][C]0.8[/C][C]0.841772151898734[/C][C]0.0384615384615385[/C][/ROW]
[ROW][C]0.81[/C][C]0.848101265822785[/C][C]0.0384615384615385[/C][/ROW]
[ROW][C]0.82[/C][C]0.854430379746835[/C][C]0.0307692307692308[/C][/ROW]
[ROW][C]0.83[/C][C]0.873417721518987[/C][C]0.0230769230769231[/C][/ROW]
[ROW][C]0.84[/C][C]0.89873417721519[/C][C]0.00769230769230769[/C][/ROW]
[ROW][C]0.85[/C][C]0.91139240506329[/C][C]0.00769230769230769[/C][/ROW]
[ROW][C]0.86[/C][C]0.917721518987342[/C][C]0.00769230769230769[/C][/ROW]
[ROW][C]0.87[/C][C]0.949367088607595[/C][C]0.00769230769230769[/C][/ROW]
[ROW][C]0.88[/C][C]0.949367088607595[/C][C]0[/C][/ROW]
[ROW][C]0.89[/C][C]0.968354430379747[/C][C]0[/C][/ROW]
[ROW][C]0.9[/C][C]0.974683544303797[/C][C]0[/C][/ROW]
[ROW][C]0.91[/C][C]0.981012658227848[/C][C]0[/C][/ROW]
[ROW][C]0.92[/C][C]0.987341772151899[/C][C]0[/C][/ROW]
[ROW][C]0.93[/C][C]0.99367088607595[/C][C]0[/C][/ROW]
[ROW][C]0.94[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]0.95[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]0.96[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]0.97[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]0.98[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]0.99[/C][C]1[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156134&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156134&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Type I & II errors for various threshold values
ThresholdType IType II
0.0101
0.0201
0.0301
0.0401
0.0500.984615384615385
0.0600.976923076923077
0.0700.96923076923077
0.0800.961538461538462
0.0900.953846153846154
0.100.953846153846154
0.1100.953846153846154
0.120.006329113924050630.938461538461538
0.130.01898734177215190.938461538461538
0.140.01898734177215190.923076923076923
0.150.02531645569620250.923076923076923
0.160.02531645569620250.907692307692308
0.170.02531645569620250.892307692307692
0.180.02531645569620250.892307692307692
0.190.02531645569620250.884615384615385
0.20.02531645569620250.861538461538462
0.210.02531645569620250.838461538461538
0.220.02531645569620250.823076923076923
0.230.02531645569620250.815384615384615
0.240.03164556962025320.792307692307692
0.250.04430379746835440.784615384615385
0.260.04430379746835440.776923076923077
0.270.05063291139240510.730769230769231
0.280.05063291139240510.707692307692308
0.290.05696202531645570.707692307692308
0.30.06329113924050630.676923076923077
0.310.07594936708860760.653846153846154
0.320.08227848101265820.646153846153846
0.330.08227848101265820.646153846153846
0.340.08860759493670890.638461538461538
0.350.09493670886075950.63076923076923
0.360.09493670886075950.623076923076923
0.370.101265822784810.6
0.380.1075949367088610.569230769230769
0.390.1139240506329110.561538461538462
0.40.1392405063291140.553846153846154
0.410.1392405063291140.523076923076923
0.420.1392405063291140.492307692307692
0.430.1518987341772150.469230769230769
0.440.1645569620253160.461538461538462
0.450.1645569620253160.461538461538462
0.460.1772151898734180.446153846153846
0.470.1772151898734180.415384615384615
0.480.1835443037974680.407692307692308
0.490.196202531645570.392307692307692
0.50.202531645569620.392307692307692
0.510.2088607594936710.384615384615385
0.520.2215189873417720.376923076923077
0.530.2341772151898730.353846153846154
0.540.2468354430379750.346153846153846
0.550.2594936708860760.338461538461538
0.560.2784810126582280.338461538461538
0.570.297468354430380.330769230769231
0.580.3164556962025320.315384615384615
0.590.3481012658227850.315384615384615
0.60.3481012658227850.3
0.610.3670886075949370.3
0.620.3734177215189870.276923076923077
0.630.3797468354430380.261538461538462
0.640.398734177215190.253846153846154
0.650.4113924050632910.2
0.660.4240506329113920.184615384615385
0.670.4430379746835440.146153846153846
0.680.4683544303797470.146153846153846
0.690.5189873417721520.130769230769231
0.70.5443037974683540.115384615384615
0.710.5886075949367090.115384615384615
0.720.594936708860760.107692307692308
0.730.6265822784810130.0923076923076923
0.740.6708860759493670.0615384615384615
0.750.702531645569620.0615384615384615
0.760.7215189873417720.0538461538461538
0.770.7594936708860760.0461538461538462
0.780.7848101265822780.0461538461538462
0.790.8354430379746840.0384615384615385
0.80.8417721518987340.0384615384615385
0.810.8481012658227850.0384615384615385
0.820.8544303797468350.0307692307692308
0.830.8734177215189870.0230769230769231
0.840.898734177215190.00769230769230769
0.850.911392405063290.00769230769230769
0.860.9177215189873420.00769230769230769
0.870.9493670886075950.00769230769230769
0.880.9493670886075950
0.890.9683544303797470
0.90.9746835443037970
0.910.9810126582278480
0.920.9873417721518990
0.930.993670886075950
0.9410
0.9510
0.9610
0.9710
0.9810
0.9910


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
library(brglm)
roc.plot <- function (sd, sdc, newplot = TRUE, ...)
{
sall <- sort(c(sd, sdc))
sens <- 0
specc <- 0
for (i in length(sall):1) {
sens <- c(sens, mean(sd >= sall[i], na.rm = T))
specc <- c(specc, mean(sdc >= sall[i], na.rm = T))
}
if (newplot) {
plot(specc, sens, xlim = c(0, 1), ylim = c(0, 1), type = 'l',
xlab = '1-specificity', ylab = 'sensitivity', main = 'ROC plot', ...)
abline(0, 1)
}
else lines(specc, sens, ...)
npoints <- length(sens)
area <- sum(0.5 * (sens[-1] + sens[-npoints]) * (specc[-1] -
specc[-npoints]))
lift <- (sens - specc)[-1]
cutoff <- sall[lift == max(lift)][1]
sensopt <- sens[-1][lift == max(lift)][1]
specopt <- 1 - specc[-1][lift == max(lift)][1]
list(area = area, cutoff = cutoff, sensopt = sensopt, specopt = specopt)
}
roc.analysis <- function (object, newdata = NULL, newplot = TRUE, ...)
{
if (is.null(newdata)) {
sd <- object$fitted[object$y == 1]
sdc <- object$fitted[object$y == 0]
}
else {
sd <- predict(object, newdata, type = 'response')[newdata$y ==
1]
sdc <- predict(object, newdata, type = 'response')[newdata$y ==
0]
}
roc.plot(sd, sdc, newplot, ...)
}
hosmerlem <- function (y, yhat, g = 10)
{
cutyhat <- cut(yhat, breaks = quantile(yhat, probs = seq(0,
1, 1/g)), include.lowest = T)
obs <- xtabs(cbind(1 - y, y) ~ cutyhat)
expect <- xtabs(cbind(1 - yhat, yhat) ~ cutyhat)
chisq <- sum((obs - expect)^2/expect)
P <- 1 - pchisq(chisq, g - 2)
c('X^2' = chisq, Df = g - 2, 'P(>Chi)' = P)
}
x <- as.data.frame(t(y))
r <- brglm(x)
summary(r)
rc <- summary(r)$coeff
try(hm <- hosmerlem(y[1,],r$fitted.values),silent=T)
try(hm,silent=T)
bitmap(file='test0.png')
ra <- roc.analysis(r)
dev.off()
te <- array(0,dim=c(2,99))
for (i in 1:99) {
threshold <- i / 100
numcorr1 <- 0
numfaul1 <- 0
numcorr0 <- 0
numfaul0 <- 0
for (j in 1:length(r$fitted.values)) {
if (y[1,j] > 0.99) {
if (r$fitted.values[j] >= threshold) numcorr1 = numcorr1 + 1 else numfaul1 = numfaul1 + 1
} else {
if (r$fitted.values[j] < threshold) numcorr0 = numcorr0 + 1 else numfaul0 = numfaul0 + 1
}
}
te[1,i] <- numfaul1 / (numfaul1 + numcorr1)
te[2,i] <- numfaul0 / (numfaul0 + numcorr0)
}
bitmap(file='test1.png')
op <- par(mfrow=c(2,2))
plot((1:99)/100,te[1,],xlab='Threshold',ylab='Type I error', main='1 - Specificity')
plot((1:99)/100,te[2,],xlab='Threshold',ylab='Type II error', main='1 - Sensitivity')
plot(te[1,],te[2,],xlab='Type I error',ylab='Type II error', main='(1-Sens.) vs (1-Spec.)')
plot((1:99)/100,te[1,]+te[2,],xlab='Threshold',ylab='Sum of Type I & II error', main='(1-Sens.) + (1-Spec.)')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Coefficients of Bias-Reduced Logistic Regression',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'t-stat',header=TRUE)
a<-table.element(a,'2-sided p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(rc[,1])) {
a<-table.row.start(a)
a<-table.element(a,labels(rc)[[1]][i],header=TRUE)
a<-table.element(a,rc[i,1])
a<-table.element(a,rc[i,2])
a<-table.element(a,rc[i,3])
a<-table.element(a,2*(1-pt(abs(rc[i,3]),r$df.residual)))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Bias-Reduced Logistic Regression',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Deviance',1,TRUE)
a<-table.element(a,r$deviance)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Penalized deviance',1,TRUE)
a<-table.element(a,r$penalized.deviance)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Residual Degrees of Freedom',1,TRUE)
a<-table.element(a,r$df.residual)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'ROC Area',1,TRUE)
a<-table.element(a,ra$area)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Hosmer–Lemeshow test',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Chi-square',1,TRUE)
phm <- array('NA',dim=3)
for (i in 1:3) { try(phm[i] <- hm[i],silent=T) }
a<-table.element(a,phm[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degrees of Freedom',1,TRUE)
a<-table.element(a,phm[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'P(>Chi)',1,TRUE)
a<-table.element(a,phm[3])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Fit of Logistic Regression',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Index',1,TRUE)
a<-table.element(a,'Actual',1,TRUE)
a<-table.element(a,'Fitted',1,TRUE)
a<-table.element(a,'Error',1,TRUE)
a<-table.row.end(a)
for (i in 1:length(r$fitted.values)) {
a<-table.row.start(a)
a<-table.element(a,i,1,TRUE)
a<-table.element(a,y[1,i])
a<-table.element(a,r$fitted.values[i])
a<-table.element(a,y[1,i]-r$fitted.values[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Type I & II errors for various threshold values',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Threshold',1,TRUE)
a<-table.element(a,'Type I',1,TRUE)
a<-table.element(a,'Type II',1,TRUE)
a<-table.row.end(a)
for (i in 1:99) {
a<-table.row.start(a)
a<-table.element(a,i/100,1,TRUE)
a<-table.element(a,te[1,i])
a<-table.element(a,te[2,i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable3.tab')