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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 04 Sep 2017 15:52:48 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Sep/04/t1504533193u80p8bsllzq38t5.htm/, Retrieved Thu, 31 Oct 2024 23:40:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307579, Retrieved Thu, 31 Oct 2024 23:40:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact201
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard dev-mean...] [2017-09-04 13:52:48] [862c2bbb722fdc3c62dece8e2749f4b3] [Current]
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Dataseries X:
6396
6509
7018
6791
6300
6737
6399
6758
6601
6891
6789
5967
6995
6771
7360
7162
7025
7188
6801
7395
7203
7534
7267
6741
7185
7295
7660
7344
7439
7264
7192
7368
7246
7625
7153
6875
7413
6981
7651
7148
7072
6943
7022
6925
6904
7666
7112
6907
7880
7261
7478
7742
7499
7563
7812
7582
7362
7779
7681
7795
8049
7541
7869
7855
7582
7723
8195
7729
7856
7984
7401
8162
8223
7743
8249
8137
7650
7689
7901
7951
7956
7908
7887
8198
8358
7837
8169
8040
8112
8348
8548
8498
8167
8331
8070
7936
8553
8108
8341
8260
8113
8042
8467
8333
8243
8517
8120
8012
8801
8115
8161
8271
8108
7992
8239
8419
8781
8992
7966
8626
7935
8166
8411
8693
8861
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307579&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307579&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307579&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16596.33333333333294.8291749882341051
27120.16666666667257.851202099665793
37303.83333333333211.550481116461785
47145.33333333333278.254407245447762
57619.5193.981020627371619
67828.83333333333246.54847700838794
77957.66666666667206.450228795458599
88201.16666666667219.022553148937711
98259.08333333333185.926895865178541
108372.58333333333346.3884992667081026
118413.2377.028115662479926
12NaNNA-Inf

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6596.33333333333 & 294.829174988234 & 1051 \tabularnewline
2 & 7120.16666666667 & 257.851202099665 & 793 \tabularnewline
3 & 7303.83333333333 & 211.550481116461 & 785 \tabularnewline
4 & 7145.33333333333 & 278.254407245447 & 762 \tabularnewline
5 & 7619.5 & 193.981020627371 & 619 \tabularnewline
6 & 7828.83333333333 & 246.54847700838 & 794 \tabularnewline
7 & 7957.66666666667 & 206.450228795458 & 599 \tabularnewline
8 & 8201.16666666667 & 219.022553148937 & 711 \tabularnewline
9 & 8259.08333333333 & 185.926895865178 & 541 \tabularnewline
10 & 8372.58333333333 & 346.388499266708 & 1026 \tabularnewline
11 & 8413.2 & 377.028115662479 & 926 \tabularnewline
12 & NaN & NA & -Inf \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307579&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]6596.33333333333[/C][C]294.829174988234[/C][C]1051[/C][/ROW]
[ROW][C]2[/C][C]7120.16666666667[/C][C]257.851202099665[/C][C]793[/C][/ROW]
[ROW][C]3[/C][C]7303.83333333333[/C][C]211.550481116461[/C][C]785[/C][/ROW]
[ROW][C]4[/C][C]7145.33333333333[/C][C]278.254407245447[/C][C]762[/C][/ROW]
[ROW][C]5[/C][C]7619.5[/C][C]193.981020627371[/C][C]619[/C][/ROW]
[ROW][C]6[/C][C]7828.83333333333[/C][C]246.54847700838[/C][C]794[/C][/ROW]
[ROW][C]7[/C][C]7957.66666666667[/C][C]206.450228795458[/C][C]599[/C][/ROW]
[ROW][C]8[/C][C]8201.16666666667[/C][C]219.022553148937[/C][C]711[/C][/ROW]
[ROW][C]9[/C][C]8259.08333333333[/C][C]185.926895865178[/C][C]541[/C][/ROW]
[ROW][C]10[/C][C]8372.58333333333[/C][C]346.388499266708[/C][C]1026[/C][/ROW]
[ROW][C]11[/C][C]8413.2[/C][C]377.028115662479[/C][C]926[/C][/ROW]
[ROW][C]12[/C][C]NaN[/C][C]NA[/C][C]-Inf[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307579&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307579&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
16596.33333333333294.8291749882341051
27120.16666666667257.851202099665793
37303.83333333333211.550481116461785
47145.33333333333278.254407245447762
57619.5193.981020627371619
67828.83333333333246.54847700838794
77957.66666666667206.450228795458599
88201.16666666667219.022553148937711
98259.08333333333185.926895865178541
108372.58333333333346.3884992667081026
118413.2377.028115662479926
12NaNNA-Inf







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha167.574614975842
beta0.0114894684846448
S.D.0.0345369046383005
T-STAT0.332672212665616
p-value0.746999604475699

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 167.574614975842 \tabularnewline
beta & 0.0114894684846448 \tabularnewline
S.D. & 0.0345369046383005 \tabularnewline
T-STAT & 0.332672212665616 \tabularnewline
p-value & 0.746999604475699 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307579&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]167.574614975842[/C][/ROW]
[ROW][C]beta[/C][C]0.0114894684846448[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0345369046383005[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.332672212665616[/C][/ROW]
[ROW][C]p-value[/C][C]0.746999604475699[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307579&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307579&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)
alpha167.574614975842
beta0.0114894684846448
S.D.0.0345369046383005
T-STAT0.332672212665616
p-value0.746999604475699







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha5.01409450015986
beta0.0565573822964264
S.D.0.978892147221378
T-STAT0.0577769292122392
p-value0.955188769125242
Lambda0.943442617703574

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.01409450015986 \tabularnewline
beta & 0.0565573822964264 \tabularnewline
S.D. & 0.978892147221378 \tabularnewline
T-STAT & 0.0577769292122392 \tabularnewline
p-value & 0.955188769125242 \tabularnewline
Lambda & 0.943442617703574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307579&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.01409450015986[/C][/ROW]
[ROW][C]beta[/C][C]0.0565573822964264[/C][/ROW]
[ROW][C]S.D.[/C][C]0.978892147221378[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0577769292122392[/C][/ROW]
[ROW][C]p-value[/C][C]0.955188769125242[/C][/ROW]
[ROW][C]Lambda[/C][C]0.943442617703574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307579&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307579&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)
alpha5.01409450015986
beta0.0565573822964264
S.D.0.978892147221378
T-STAT0.0577769292122392
p-value0.955188769125242
Lambda0.943442617703574



Parameters (Session):
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')