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Description of Statistical Computation

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 computationWed, 22 Dec 2010 08:54:19 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/22/t1293008047bfht2jqrh0aag72.htm/, Retrieved Mon, 06 May 2024 08:50:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114121, Retrieved Mon, 06 May 2024 08:50:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

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] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   PD      [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-12-22 08:54:19] [2e87ce7aa3eb3dfe16df617f31f74f3c] [Current]
-    D        [Standard Deviation-Mean Plot] [SMP Olieprijs] [2010-12-25 20:34:58] [ae68acb0755efbaaf8db92ef09a2ce40]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
175.348
154.439
136.186
113.662
106.157
100.546
98.314
118.179
112.295
126.938
130.92
181.279
180.389
146.917
150.597
124.222
101.554
102.138
110.315
111.015
105.017
119.888
127.623
149.415
159.755
139.737
136.283
101.952
104.044
96.712
100.665
103.699
103.765
122.732
127.297
160.278
191.784
155.375
142.616
115.331
102.136
95.205
101.566
105.273
117.394
121.148
116.666
154.841
177.74
154.427
133.159
118.102
101.361
101.345
102.233
108.522
101.939
118.405
125.06
178
167.714
143.582
139.259
104.674
103.722
106.153
106.21
113.986
96.906
107.512
112.616
148.507
130.48
137.436
128.21
97.552
91.55
83.104
84.68
85.98
84.891
89.896
94.835
115.348
131.284
134.701
127.193
87.077
72.744
77.542
78.005
85.329
86.041
96.384
116.678
160.672
152.364
144.936
122.974
94.456
82.491
84.89
85.277
81.206
71.012
87.302
97.427
133.242
137.064
119.042
116.47
96.028
79.281
73.872
80.964
86.739
89.997
96.292
101.355
136.543

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114121&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114121&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114121&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1129.52191666666727.780225820334682.965
2127.42416666666724.579425046287478.835
3121.40991666666723.198968344845763.566
4126.6112528.820516937907096.579
5126.69108333333328.635356284458576.655
6120.90341666666722.700096937952170.808
7101.99683333333320.147601530312354.332
8104.47083333333328.544856243633487.928
9103.13141666666727.66710640801581.352
10101.1372521.55134335034763.192

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 129.521916666667 & 27.7802258203346 & 82.965 \tabularnewline
2 & 127.424166666667 & 24.5794250462874 & 78.835 \tabularnewline
3 & 121.409916666667 & 23.1989683448457 & 63.566 \tabularnewline
4 & 126.61125 & 28.8205169379070 & 96.579 \tabularnewline
5 & 126.691083333333 & 28.6353562844585 & 76.655 \tabularnewline
6 & 120.903416666667 & 22.7000969379521 & 70.808 \tabularnewline
7 & 101.996833333333 & 20.1476015303123 & 54.332 \tabularnewline
8 & 104.470833333333 & 28.5448562436334 & 87.928 \tabularnewline
9 & 103.131416666667 & 27.667106408015 & 81.352 \tabularnewline
10 & 101.13725 & 21.551343350347 & 63.192 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114121&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]129.521916666667[/C][C]27.7802258203346[/C][C]82.965[/C][/ROW]
[ROW][C]2[/C][C]127.424166666667[/C][C]24.5794250462874[/C][C]78.835[/C][/ROW]
[ROW][C]3[/C][C]121.409916666667[/C][C]23.1989683448457[/C][C]63.566[/C][/ROW]
[ROW][C]4[/C][C]126.61125[/C][C]28.8205169379070[/C][C]96.579[/C][/ROW]
[ROW][C]5[/C][C]126.691083333333[/C][C]28.6353562844585[/C][C]76.655[/C][/ROW]
[ROW][C]6[/C][C]120.903416666667[/C][C]22.7000969379521[/C][C]70.808[/C][/ROW]
[ROW][C]7[/C][C]101.996833333333[/C][C]20.1476015303123[/C][C]54.332[/C][/ROW]
[ROW][C]8[/C][C]104.470833333333[/C][C]28.5448562436334[/C][C]87.928[/C][/ROW]
[ROW][C]9[/C][C]103.131416666667[/C][C]27.667106408015[/C][C]81.352[/C][/ROW]
[ROW][C]10[/C][C]101.13725[/C][C]21.551343350347[/C][C]63.192[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114121&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114121&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
1129.52191666666727.780225820334682.965
2127.42416666666724.579425046287478.835
3121.40991666666723.198968344845763.566
4126.6112528.820516937907096.579
5126.69108333333328.635356284458576.655
6120.90341666666722.700096937952170.808
7101.99683333333320.147601530312354.332
8104.47083333333328.544856243633487.928
9103.13141666666727.66710640801581.352
10101.1372521.55134335034763.192






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha13.4454335919394
beta0.102442497492323
S.D.0.0897723960017518
T-STAT1.14113582854938
p-value0.286819276033267

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 13.4454335919394 \tabularnewline
beta & 0.102442497492323 \tabularnewline
S.D. & 0.0897723960017518 \tabularnewline
T-STAT & 1.14113582854938 \tabularnewline
p-value & 0.286819276033267 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114121&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.4454335919394[/C][/ROW]
[ROW][C]beta[/C][C]0.102442497492323[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0897723960017518[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.14113582854938[/C][/ROW]
[ROW][C]p-value[/C][C]0.286819276033267[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114121&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114121&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)
alpha13.4454335919394
beta0.102442497492323
S.D.0.0897723960017518
T-STAT1.14113582854938
p-value0.286819276033267






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.880466976793943
beta0.493510325158011
S.D.0.412572525780603
T-STAT1.19617835488263
p-value0.265873584844966
Lambda0.506489674841989

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.880466976793943 \tabularnewline
beta & 0.493510325158011 \tabularnewline
S.D. & 0.412572525780603 \tabularnewline
T-STAT & 1.19617835488263 \tabularnewline
p-value & 0.265873584844966 \tabularnewline
Lambda & 0.506489674841989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114121&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.880466976793943[/C][/ROW]
[ROW][C]beta[/C][C]0.493510325158011[/C][/ROW]
[ROW][C]S.D.[/C][C]0.412572525780603[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.19617835488263[/C][/ROW]
[ROW][C]p-value[/C][C]0.265873584844966[/C][/ROW]
[ROW][C]Lambda[/C][C]0.506489674841989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114121&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114121&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)
alpha0.880466976793943
beta0.493510325158011
S.D.0.412572525780603
T-STAT1.19617835488263
p-value0.265873584844966
Lambda0.506489674841989


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')