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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 12 Aug 2016 20:21:24 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/12/t1471029723g9hjbuq6bb03ji8.htm/, Retrieved Sun, 05 May 2024 18:28:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296462, Retrieved Sun, 05 May 2024 18:28:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Omzet Mentos Aardbei] [2016-07-17 11:11:37] [74be16979710d4c4e7c6647856088456]
-   P   [Univariate Data Series] [Omzet Mentos Aardbei] [2016-08-02 12:13:56] [74be16979710d4c4e7c6647856088456]
-   P     [Univariate Data Series] [] [2016-08-12 10:07:18] [74be16979710d4c4e7c6647856088456]
- R  D      [Univariate Data Series] [] [2016-08-12 10:23:50] [74be16979710d4c4e7c6647856088456]
- RMP           [Standard Deviation-Mean Plot] [] [2016-08-12 19:21:24] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
425.25
417.75
410.25
395.25
546.75
539.25
425.25
349.50
357.00
357.00
364.50
380.25
334.50
288.75
251.25
251.25
395.25
410.25
296.25
167.25
235.50
235.50
288.75
319.50
312.00
235.50
273.75
258.75
387.75
357.00
235.50
144.75
228.00
251.25
273.75
303.75
243.00
190.50
213.00
220.50
417.75
417.75
303.75
288.75
334.50
312.00
372.75
448.50
463.50
357.00
327.00
296.25
501.75
516.75
478.50
516.75
509.25
448.50
516.75
592.50
623.25
531.75
471.00
516.75
714.00
774.75
759.75
789.75
782.25
706.50
835.50
866.25
911.25
774.75
721.50
782.25
927.00
1056.00
1025.25
1025.25
1040.25
987.75
1124.25
1124.25
1101.00
972.00
995.25
1010.25
1109.25
1238.25
1146.75
1192.50
1154.25
1131.75
1306.50
1268.25
1215.00
1139.25
1215.00
1253.25
1299.00
1359.75
1299.00
1336.50
1290.75
1283.25
1473.00
1488.75
1428.00
1321.50
1412.25
1450.50
1496.25
1564.50
1496.25
1549.50
1526.25
1443.00
1617.75
1617.75

Tables (Output of Computation)





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=296462&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=296462&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296462&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
141466.1887796039068197.25
2289.569.0444520844098243
3271.812563.7010172781623243
4313.562587.1107005351654258
5460.37588.9247319621794296.25
6697.625131.55289724186395.25
7958.3125136.556229053024402.75
81135.5106.656415227078334.5
91304.375101.386944425799349.5
101493.62587.9130187380479296.25

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 414 & 66.1887796039068 & 197.25 \tabularnewline
2 & 289.5 & 69.0444520844098 & 243 \tabularnewline
3 & 271.8125 & 63.7010172781623 & 243 \tabularnewline
4 & 313.5625 & 87.1107005351654 & 258 \tabularnewline
5 & 460.375 & 88.9247319621794 & 296.25 \tabularnewline
6 & 697.625 & 131.55289724186 & 395.25 \tabularnewline
7 & 958.3125 & 136.556229053024 & 402.75 \tabularnewline
8 & 1135.5 & 106.656415227078 & 334.5 \tabularnewline
9 & 1304.375 & 101.386944425799 & 349.5 \tabularnewline
10 & 1493.625 & 87.9130187380479 & 296.25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296462&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]414[/C][C]66.1887796039068[/C][C]197.25[/C][/ROW]
[ROW][C]2[/C][C]289.5[/C][C]69.0444520844098[/C][C]243[/C][/ROW]
[ROW][C]3[/C][C]271.8125[/C][C]63.7010172781623[/C][C]243[/C][/ROW]
[ROW][C]4[/C][C]313.5625[/C][C]87.1107005351654[/C][C]258[/C][/ROW]
[ROW][C]5[/C][C]460.375[/C][C]88.9247319621794[/C][C]296.25[/C][/ROW]
[ROW][C]6[/C][C]697.625[/C][C]131.55289724186[/C][C]395.25[/C][/ROW]
[ROW][C]7[/C][C]958.3125[/C][C]136.556229053024[/C][C]402.75[/C][/ROW]
[ROW][C]8[/C][C]1135.5[/C][C]106.656415227078[/C][C]334.5[/C][/ROW]
[ROW][C]9[/C][C]1304.375[/C][C]101.386944425799[/C][C]349.5[/C][/ROW]
[ROW][C]10[/C][C]1493.625[/C][C]87.9130187380479[/C][C]296.25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296462&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296462&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:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
141466.1887796039068197.25
2289.569.0444520844098243
3271.812563.7010172781623243
4313.562587.1107005351654258
5460.37588.9247319621794296.25
6697.625131.55289724186395.25
7958.3125136.556229053024402.75
81135.5106.656415227078334.5
91304.375101.386944425799349.5
101493.62587.9130187380479296.25






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha73.9483812282871
beta0.0271916979523601
S.D.0.0172378723592584
T-STAT1.57743933738757
p-value0.153345983317549

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 73.9483812282871 \tabularnewline
beta & 0.0271916979523601 \tabularnewline
S.D. & 0.0172378723592584 \tabularnewline
T-STAT & 1.57743933738757 \tabularnewline
p-value & 0.153345983317549 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296462&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]73.9483812282871[/C][/ROW]
[ROW][C]beta[/C][C]0.0271916979523601[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0172378723592584[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.57743933738757[/C][/ROW]
[ROW][C]p-value[/C][C]0.153345983317549[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296462&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296462&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:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha73.9483812282871
beta0.0271916979523601
S.D.0.0172378723592584
T-STAT1.57743933738757
p-value0.153345983317549






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.79350616016542
beta0.267705640056894
S.D.0.109128724139778
T-STAT2.45311802339044
p-value0.0397429998095874
Lambda0.732294359943106

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.79350616016542 \tabularnewline
beta & 0.267705640056894 \tabularnewline
S.D. & 0.109128724139778 \tabularnewline
T-STAT & 2.45311802339044 \tabularnewline
p-value & 0.0397429998095874 \tabularnewline
Lambda & 0.732294359943106 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296462&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.79350616016542[/C][/ROW]
[ROW][C]beta[/C][C]0.267705640056894[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109128724139778[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.45311802339044[/C][/ROW]
[ROW][C]p-value[/C][C]0.0397429998095874[/C][/ROW]
[ROW][C]Lambda[/C][C]0.732294359943106[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296462&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296462&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:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.79350616016542
beta0.267705640056894
S.D.0.109128724139778
T-STAT2.45311802339044
p-value0.0397429998095874
Lambda0.732294359943106


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
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')