Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationTue, 22 Nov 2011 12:33:37 -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/Nov/22/t1321983304abjnsp3730dgorv.htm/, Retrieved Wed, 24 Apr 2024 09:52:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146334, Retrieved Wed, 24 Apr 2024 09:52:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [SHWWS2/1] [2009-10-12 16:52:29] [9717cb857c153ca3061376906953b329]
-   PD  [Univariate Data Series] [Aantal niet-werke...] [2009-10-24 19:05:50] [9717cb857c153ca3061376906953b329]
-  MPD    [Univariate Data Series] [Aantal inschrijvi...] [2009-11-05 03:01:41] [9717cb857c153ca3061376906953b329]
- RMPD      [Bivariate Explorative Data Analysis] [WS 5] [2009-11-05 03:11:20] [9717cb857c153ca3061376906953b329]
- R  D          [Bivariate Explorative Data Analysis] [] [2011-11-22 17:33:37] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataseries X:
1173
669
1154
1948
722
336
2727
345
1416
1208
1432
1246
1205
1732
1214
3222
1385
2011
884
1631
1460
1950
860
1165
2115
1940
1858
1347
1093
1650
1551
1273
1478
670
2040
1562
2079
1113
686
2066
2251
1107
1245
1021
1735
3681
918
1582
2900
1497
1116
496
1778
744
1104
1703
1871
2460
1705
1334
2647
2218
1635
1741
991
1195
1283
1992
1522
1071
1441
852
1425
1246
1100
1400
1556
1015
1002
1190
1244
2657
1232
1344
870
1474
881
2489
1444
1995
1258
1357
1329
2041
1454
1171
1219
1522
2314
2289
1371
1639
1000
602
1380
1208
1490
1801
728
1152
1277
1401
391
1264
530
1123
2055
387
1486
449
2212
1148
814
1015
568
936
1586
871
2276
1638
2238
838
841
1904
3054
655
2617
1314
1154
1497
754
2832
1281
2035
1894
1268
1714
1568
0
207
5
8
0
0
1302
1831
0
4
151
474
141
705
29
1033
Dataseries Y:
170650
86621
127843
152526
92389
38778
316392
32750
123444
137034
176816
143205
113286
195452
144513
263581
183271
210763
113853
159968
174585
294675
96213
116390
146342
152647
166661
175505
112485
198790
191822
140267
221991
75339
247985
167351
266609
122024
80964
215183
225469
125382
141437
81106
93125
318668
78800
161048
236367
131108
131096
24188
267003
65029
100147
178549
186965
197266
217300
149594
263413
209228
145699
187197
150752
131218
118697
147913
155015
96487
128780
71972
140266
152455
110655
204822
216052
113421
103660
128390
105502
299359
141493
148356
80953
109237
102104
233139
176507
118217
142694
152193
126500
174710
187772
140903
155350
202077
213875
252952
166981
190790
106351
43287
127493
132143
157469
197727
88077
94968
191753
153332
22938
125927
61857
103749
269909
21054
174409
31414
200405
139456
78001
82724
38214
91390
197612
137161
251103
209835
269470
139215
77796
197114
291962
56727
254843
105908
170155
136745
86706
251448
152366
173260
212582
87850
148636
185455
0
14688
98
455
0
0
137891
201052
0
203
7199
46660
17547
73567
969
106662




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146334&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146334&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146334&T=0

As an alternative you can also use a 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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Model: Y[t] = c + b X[t] + e[t]
c11437.833288531
b96.3908009401442

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 11437.833288531 \tabularnewline
b & 96.3908009401442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146334&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]11437.833288531[/C][/ROW]
[ROW][C]b[/C][C]96.3908009401442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146334&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146334&T=1

As an alternative you can also use a QR Code:  

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

Model: Y[t] = c + b X[t] + e[t]
c11437.833288531
b96.3908009401442







Descriptive Statistics about e[t]
# observations164
minimum-85550.8729196811
Q1-17916.0032252436
median-2178.85730225711
mean7.34772676307285e-13
Q317100.3992824499
maximum95275.1048781879

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 164 \tabularnewline
minimum & -85550.8729196811 \tabularnewline
Q1 & -17916.0032252436 \tabularnewline
median & -2178.85730225711 \tabularnewline
mean & 7.34772676307285e-13 \tabularnewline
Q3 & 17100.3992824499 \tabularnewline
maximum & 95275.1048781879 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146334&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]164[/C][/ROW]
[ROW][C]minimum[/C][C]-85550.8729196811[/C][/ROW]
[ROW][C]Q1[/C][C]-17916.0032252436[/C][/ROW]
[ROW][C]median[/C][C]-2178.85730225711[/C][/ROW]
[ROW][C]mean[/C][C]7.34772676307285e-13[/C][/ROW]
[ROW][C]Q3[/C][C]17100.3992824499[/C][/ROW]
[ROW][C]maximum[/C][C]95275.1048781879[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146334&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146334&T=2

As an alternative you can also use a QR Code:  

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

Descriptive Statistics about e[t]
# observations164
minimum-85550.8729196811
Q1-17916.0032252436
median-2178.85730225711
mean7.34772676307285e-13
Q317100.3992824499
maximum95275.1048781879



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
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,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')