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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 computationWed, 23 Dec 2009 07:54:41 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/23/t1261580110h5uxl2696z7eswg.htm/, Retrieved Mon, 29 Apr 2024 08:32:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70541, Retrieved Mon, 29 Apr 2024 08:32:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact101

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Mean cosmetics] [2009-12-23 14:54:41] [dd4c09afc8b527b51f4c8ef6a655ef42] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
84.9
81.9
95.9
81
89.2
102.5
89.8
88.8
83.2
90.2
100.4
187.1
87.6
85.4
86.1
86.7
89.1
103.7
86.9
85.2
80.8
91.2
102.8
182.5
80.9
83.1
88.3
86.6
93
105.3
93.8
86.4
87
96.7
100.5
196.7
86.8
88.2
93.8
85
90.4
115.9
94.9
87.7
91.7
95.9
106.8
204.5
90.2
90.5
93.2
97.8
99.4
120
108.2
98.5
104.3
102.9
111.1
188.1
93.8
94.5
112.4
102.5
115.8
136.5
122.1
110.6
116.4
112.6
121.5
199.3
102.1
100.6
119
106.8
121.3
145.5
129.7
117.7
121.3
124.3
135.2
210.1
106.8
110.5
111.5
122.1
126.3
143.2
137.3
121.5
121.9
123.9
131.6
220.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70541&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70541&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
185.9256.8558369292158714.9
292.5756.629416766704813.7
3115.22548.434311185357103.9
486.450.9327379053088782.19999999999999
591.2258.4685201383319218.5
6114.32546.329787034549101.7
784.7253.345021175817377.39999999999999
894.6257.8512737820050518.9
9120.22551.2992121446974109.7
1088.453.799561378194428.8
1197.22512.799316387995128.2
12124.72553.562696907456112.8
1392.9253.518877661982587.6
14106.5259.9924554873497821.5
15126.641.156125506012785.2
16100.88.682165628459318.6
17121.2511.201339205648625.9
18137.4541.394242755887486.7
19107.1258.3456076271693218.4
20128.5512.368104139277027.8
21147.72542.010028564617888.8
22112.7256.568802529127115.3
23132.0759.9372615275369821.7
24149.57547.733522462381499

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 85.925 & 6.85583692921587 & 14.9 \tabularnewline
2 & 92.575 & 6.6294167667048 & 13.7 \tabularnewline
3 & 115.225 & 48.434311185357 & 103.9 \tabularnewline
4 & 86.45 & 0.932737905308878 & 2.19999999999999 \tabularnewline
5 & 91.225 & 8.46852013833192 & 18.5 \tabularnewline
6 & 114.325 & 46.329787034549 & 101.7 \tabularnewline
7 & 84.725 & 3.34502117581737 & 7.39999999999999 \tabularnewline
8 & 94.625 & 7.85127378200505 & 18.9 \tabularnewline
9 & 120.225 & 51.2992121446974 & 109.7 \tabularnewline
10 & 88.45 & 3.79956137819442 & 8.8 \tabularnewline
11 & 97.225 & 12.7993163879951 & 28.2 \tabularnewline
12 & 124.725 & 53.562696907456 & 112.8 \tabularnewline
13 & 92.925 & 3.51887766198258 & 7.6 \tabularnewline
14 & 106.525 & 9.99245548734978 & 21.5 \tabularnewline
15 & 126.6 & 41.1561255060127 & 85.2 \tabularnewline
16 & 100.8 & 8.6821656284593 & 18.6 \tabularnewline
17 & 121.25 & 11.2013392056486 & 25.9 \tabularnewline
18 & 137.45 & 41.3942427558874 & 86.7 \tabularnewline
19 & 107.125 & 8.34560762716932 & 18.4 \tabularnewline
20 & 128.55 & 12.3681041392770 & 27.8 \tabularnewline
21 & 147.725 & 42.0100285646178 & 88.8 \tabularnewline
22 & 112.725 & 6.5688025291271 & 15.3 \tabularnewline
23 & 132.075 & 9.93726152753698 & 21.7 \tabularnewline
24 & 149.575 & 47.7335224623814 & 99 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70541&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]85.925[/C][C]6.85583692921587[/C][C]14.9[/C][/ROW]
[ROW][C]2[/C][C]92.575[/C][C]6.6294167667048[/C][C]13.7[/C][/ROW]
[ROW][C]3[/C][C]115.225[/C][C]48.434311185357[/C][C]103.9[/C][/ROW]
[ROW][C]4[/C][C]86.45[/C][C]0.932737905308878[/C][C]2.19999999999999[/C][/ROW]
[ROW][C]5[/C][C]91.225[/C][C]8.46852013833192[/C][C]18.5[/C][/ROW]
[ROW][C]6[/C][C]114.325[/C][C]46.329787034549[/C][C]101.7[/C][/ROW]
[ROW][C]7[/C][C]84.725[/C][C]3.34502117581737[/C][C]7.39999999999999[/C][/ROW]
[ROW][C]8[/C][C]94.625[/C][C]7.85127378200505[/C][C]18.9[/C][/ROW]
[ROW][C]9[/C][C]120.225[/C][C]51.2992121446974[/C][C]109.7[/C][/ROW]
[ROW][C]10[/C][C]88.45[/C][C]3.79956137819442[/C][C]8.8[/C][/ROW]
[ROW][C]11[/C][C]97.225[/C][C]12.7993163879951[/C][C]28.2[/C][/ROW]
[ROW][C]12[/C][C]124.725[/C][C]53.562696907456[/C][C]112.8[/C][/ROW]
[ROW][C]13[/C][C]92.925[/C][C]3.51887766198258[/C][C]7.6[/C][/ROW]
[ROW][C]14[/C][C]106.525[/C][C]9.99245548734978[/C][C]21.5[/C][/ROW]
[ROW][C]15[/C][C]126.6[/C][C]41.1561255060127[/C][C]85.2[/C][/ROW]
[ROW][C]16[/C][C]100.8[/C][C]8.6821656284593[/C][C]18.6[/C][/ROW]
[ROW][C]17[/C][C]121.25[/C][C]11.2013392056486[/C][C]25.9[/C][/ROW]
[ROW][C]18[/C][C]137.45[/C][C]41.3942427558874[/C][C]86.7[/C][/ROW]
[ROW][C]19[/C][C]107.125[/C][C]8.34560762716932[/C][C]18.4[/C][/ROW]
[ROW][C]20[/C][C]128.55[/C][C]12.3681041392770[/C][C]27.8[/C][/ROW]
[ROW][C]21[/C][C]147.725[/C][C]42.0100285646178[/C][C]88.8[/C][/ROW]
[ROW][C]22[/C][C]112.725[/C][C]6.5688025291271[/C][C]15.3[/C][/ROW]
[ROW][C]23[/C][C]132.075[/C][C]9.93726152753698[/C][C]21.7[/C][/ROW]
[ROW][C]24[/C][C]149.575[/C][C]47.7335224623814[/C][C]99[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70541&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
185.9256.8558369292158714.9
292.5756.629416766704813.7
3115.22548.434311185357103.9
486.450.9327379053088782.19999999999999
591.2258.4685201383319218.5
6114.32546.329787034549101.7
784.7253.345021175817377.39999999999999
894.6257.8512737820050518.9
9120.22551.2992121446974109.7
1088.453.799561378194428.8
1197.22512.799316387995128.2
12124.72553.562696907456112.8
1392.9253.518877661982587.6
14106.5259.9924554873497821.5
15126.641.156125506012785.2
16100.88.682165628459318.6
17121.2511.201339205648625.9
18137.4541.394242755887486.7
19107.1258.3456076271693218.4
20128.5512.368104139277027.8
21147.72542.010028564617888.8
22112.7256.568802529127115.3
23132.0759.9372615275369821.7
24149.57547.733522462381499






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-54.9522826376345
beta0.681479492721697
S.D.0.145576097546478
T-STAT4.68125952135871
p-value0.000114299487753341

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -54.9522826376345 \tabularnewline
beta & 0.681479492721697 \tabularnewline
S.D. & 0.145576097546478 \tabularnewline
T-STAT & 4.68125952135871 \tabularnewline
p-value & 0.000114299487753341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70541&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-54.9522826376345[/C][/ROW]
[ROW][C]beta[/C][C]0.681479492721697[/C][/ROW]
[ROW][C]S.D.[/C][C]0.145576097546478[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.68125952135871[/C][/ROW]
[ROW][C]p-value[/C][C]0.000114299487753341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70541&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70541&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)
alpha-54.9522826376345
beta0.681479492721697
S.D.0.145576097546478
T-STAT4.68125952135871
p-value0.000114299487753341






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-19.9407289890110
beta4.78809974346984
S.D.0.823475174282808
T-STAT5.81450405914174
p-value7.52419482199845e-06
Lambda-3.78809974346984

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -19.9407289890110 \tabularnewline
beta & 4.78809974346984 \tabularnewline
S.D. & 0.823475174282808 \tabularnewline
T-STAT & 5.81450405914174 \tabularnewline
p-value & 7.52419482199845e-06 \tabularnewline
Lambda & -3.78809974346984 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70541&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-19.9407289890110[/C][/ROW]
[ROW][C]beta[/C][C]4.78809974346984[/C][/ROW]
[ROW][C]S.D.[/C][C]0.823475174282808[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.81450405914174[/C][/ROW]
[ROW][C]p-value[/C][C]7.52419482199845e-06[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.78809974346984[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70541&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70541&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)
alpha-19.9407289890110
beta4.78809974346984
S.D.0.823475174282808
T-STAT5.81450405914174
p-value7.52419482199845e-06
Lambda-3.78809974346984


Figures (Output of Computation)

Input Parameters & R Code

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')