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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 29 Nov 2011 07:58:13 -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/29/t1322571541xu238seredc86ym.htm/, Retrieved Fri, 29 Mar 2024 09:00:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148309, Retrieved Fri, 29 Mar 2024 09:00:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [KDGP2W83 laatste ...] [2011-11-29 12:58:13] [480fcaba71e70207c3e0ad7177944aa6] [Current]
- R P     [Standard Deviation-Mean Plot] [aanpassing 4 ipv 12 ] [2011-12-05 11:55:16] [d3f36facbecf1a8bd8ef7d895f576bb4]
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Dataseries X:
2144
2207
1864
2061
2025
2068
2054
2095
2151
2065
2147
1994
2273
2119
1969
1821
1942
1802
1737
1650
1720
1491
1570
1649
1409
1480
1495
1490
1415
1448
1354
1330
1183
1264
1197
1037
1084
1103
1005
1013
973
1046
923
844
820
777
652
560
490
582
505
478
540
585
594
586
585
534
588
581
615
603
626
687
580
539
550
606
597
539
551
526




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148309&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]1 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=148309&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148309&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12069149.173277320929343
22060.529.149042294158970
32089.2574.852632997555157
42045.5194.431650372738452
51782.75123.080935431393292
61607.598.9225286103558229
71468.540.15387071420886
81386.7554.2916506779204118
91170.2595.6081412154146227
101051.2549.506733548747398
11946.584.9725445854914202
12702.25118.62089473051260
13513.7546.8214694344379104
14576.2524.554
1557225.495097567963954
16632.7537.366428783066884
17568.7530.280631873636167
18553.2530.901725949640271

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2069 & 149.173277320929 & 343 \tabularnewline
2 & 2060.5 & 29.1490422941589 & 70 \tabularnewline
3 & 2089.25 & 74.852632997555 & 157 \tabularnewline
4 & 2045.5 & 194.431650372738 & 452 \tabularnewline
5 & 1782.75 & 123.080935431393 & 292 \tabularnewline
6 & 1607.5 & 98.9225286103558 & 229 \tabularnewline
7 & 1468.5 & 40.153870714208 & 86 \tabularnewline
8 & 1386.75 & 54.2916506779204 & 118 \tabularnewline
9 & 1170.25 & 95.6081412154146 & 227 \tabularnewline
10 & 1051.25 & 49.5067335487473 & 98 \tabularnewline
11 & 946.5 & 84.9725445854914 & 202 \tabularnewline
12 & 702.25 & 118.62089473051 & 260 \tabularnewline
13 & 513.75 & 46.8214694344379 & 104 \tabularnewline
14 & 576.25 & 24.5 & 54 \tabularnewline
15 & 572 & 25.4950975679639 & 54 \tabularnewline
16 & 632.75 & 37.3664287830668 & 84 \tabularnewline
17 & 568.75 & 30.2806318736361 & 67 \tabularnewline
18 & 553.25 & 30.9017259496402 & 71 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148309&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]2069[/C][C]149.173277320929[/C][C]343[/C][/ROW]
[ROW][C]2[/C][C]2060.5[/C][C]29.1490422941589[/C][C]70[/C][/ROW]
[ROW][C]3[/C][C]2089.25[/C][C]74.852632997555[/C][C]157[/C][/ROW]
[ROW][C]4[/C][C]2045.5[/C][C]194.431650372738[/C][C]452[/C][/ROW]
[ROW][C]5[/C][C]1782.75[/C][C]123.080935431393[/C][C]292[/C][/ROW]
[ROW][C]6[/C][C]1607.5[/C][C]98.9225286103558[/C][C]229[/C][/ROW]
[ROW][C]7[/C][C]1468.5[/C][C]40.153870714208[/C][C]86[/C][/ROW]
[ROW][C]8[/C][C]1386.75[/C][C]54.2916506779204[/C][C]118[/C][/ROW]
[ROW][C]9[/C][C]1170.25[/C][C]95.6081412154146[/C][C]227[/C][/ROW]
[ROW][C]10[/C][C]1051.25[/C][C]49.5067335487473[/C][C]98[/C][/ROW]
[ROW][C]11[/C][C]946.5[/C][C]84.9725445854914[/C][C]202[/C][/ROW]
[ROW][C]12[/C][C]702.25[/C][C]118.62089473051[/C][C]260[/C][/ROW]
[ROW][C]13[/C][C]513.75[/C][C]46.8214694344379[/C][C]104[/C][/ROW]
[ROW][C]14[/C][C]576.25[/C][C]24.5[/C][C]54[/C][/ROW]
[ROW][C]15[/C][C]572[/C][C]25.4950975679639[/C][C]54[/C][/ROW]
[ROW][C]16[/C][C]632.75[/C][C]37.3664287830668[/C][C]84[/C][/ROW]
[ROW][C]17[/C][C]568.75[/C][C]30.2806318736361[/C][C]67[/C][/ROW]
[ROW][C]18[/C][C]553.25[/C][C]30.9017259496402[/C][C]71[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148309&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148309&T=1

As an alternative you can also use a QR Code:  

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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12069149.173277320929343
22060.529.149042294158970
32089.2574.852632997555157
42045.5194.431650372738452
51782.75123.080935431393292
61607.598.9225286103558229
71468.540.15387071420886
81386.7554.2916506779204118
91170.2595.6081412154146227
101051.2549.506733548747398
11946.584.9725445854914202
12702.25118.62089473051260
13513.7546.8214694344379104
14576.2524.554
1557225.495097567963954
16632.7537.366428783066884
17568.7530.280631873636167
18553.2530.901725949640271







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha17.317000546857
beta0.0457143035665748
S.D.0.0163999192894549
T-STAT2.78747125273775
p-value0.0131774317602237

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 17.317000546857 \tabularnewline
beta & 0.0457143035665748 \tabularnewline
S.D. & 0.0163999192894549 \tabularnewline
T-STAT & 2.78747125273775 \tabularnewline
p-value & 0.0131774317602237 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148309&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]17.317000546857[/C][/ROW]
[ROW][C]beta[/C][C]0.0457143035665748[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0163999192894549[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.78747125273775[/C][/ROW]
[ROW][C]p-value[/C][C]0.0131774317602237[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148309&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148309&T=2

As an alternative you can also use a QR Code:  

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha17.317000546857
beta0.0457143035665748
S.D.0.0163999192894549
T-STAT2.78747125273775
p-value0.0131774317602237







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.928257425199446
beta0.71915014237605
S.D.0.244283804112373
T-STAT2.94391249141198
p-value0.00953047259716576
Lambda0.280849857623949

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.928257425199446 \tabularnewline
beta & 0.71915014237605 \tabularnewline
S.D. & 0.244283804112373 \tabularnewline
T-STAT & 2.94391249141198 \tabularnewline
p-value & 0.00953047259716576 \tabularnewline
Lambda & 0.280849857623949 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148309&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.928257425199446[/C][/ROW]
[ROW][C]beta[/C][C]0.71915014237605[/C][/ROW]
[ROW][C]S.D.[/C][C]0.244283804112373[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.94391249141198[/C][/ROW]
[ROW][C]p-value[/C][C]0.00953047259716576[/C][/ROW]
[ROW][C]Lambda[/C][C]0.280849857623949[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148309&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148309&T=3

As an alternative you can also use a QR Code:  

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.928257425199446
beta0.71915014237605
S.D.0.244283804112373
T-STAT2.94391249141198
p-value0.00953047259716576
Lambda0.280849857623949



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
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,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')