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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 computationThu, 01 Aug 2013 09:01:31 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Aug/01/t1375362113qzjrf71tswijay7.htm/, Retrieved Mon, 29 Apr 2024 02:43:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210877, Retrieved Mon, 29 Apr 2024 02:43:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVan Camp Stef
Estimated Impact190

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [] [2013-08-01 12:04:45] [6decc077dded9d451dc0be9ee2a4b58b]
- RM      [Standard Deviation-Mean Plot] [] [2013-08-01 13:01:31] [941d89646656d1688f5e273fb31a8e6b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
69731
68504
67277
64823
89654
88427
69731
57316
58542
58542
59770
62357
54862
47354
41207
41207
64823
67277
48581
27431
38620
38620
47354
52396
51168
38620
44900
42434
63584
58542
38620
23738
37392
41207
44900
49808
39846
31246
34939
36166
68504
68504
49808
47354
54862
51168
61130
73546
76012
58542
53622
48581
82280
84746
78466
84746
83507
73546
84746
97162
102203
87200
77238
84746
117084
127046
124592
129499
128273
115858
137008
142049
149423
127046
118312
128273
152010
173160
168119
168119
170585
161971
184361
184361
180546
159384
163199
165665
181895
203045
188041
195550
189269
185587
214246
207965
199230
186815
199230
205511
213006
222967
213006
219154
211657
210431
241542
244129
234168
216700
231581
237850
245357
256546
245357
254092
250277
236622
265279
265279

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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210877&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210877&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210877&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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
167889.510852.339718403432338
247477.666666666711322.818411856639846
344576.083333333310445.137002089739846
451422.7514282.434839053842300
575496.333333333314583.673014918448581
6114399.66666666721570.470898612364811
715714522393.636165823466049
8186199.33333333317490.216732028654862
9213889.83333333316626.21204786657314
10244925.66666666714416.186460385648579

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 67889.5 & 10852.3397184034 & 32338 \tabularnewline
2 & 47477.6666666667 & 11322.8184118566 & 39846 \tabularnewline
3 & 44576.0833333333 & 10445.1370020897 & 39846 \tabularnewline
4 & 51422.75 & 14282.4348390538 & 42300 \tabularnewline
5 & 75496.3333333333 & 14583.6730149184 & 48581 \tabularnewline
6 & 114399.666666667 & 21570.4708986123 & 64811 \tabularnewline
7 & 157145 & 22393.6361658234 & 66049 \tabularnewline
8 & 186199.333333333 & 17490.2167320286 & 54862 \tabularnewline
9 & 213889.833333333 & 16626.212047866 & 57314 \tabularnewline
10 & 244925.666666667 & 14416.1864603856 & 48579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210877&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]67889.5[/C][C]10852.3397184034[/C][C]32338[/C][/ROW]
[ROW][C]2[/C][C]47477.6666666667[/C][C]11322.8184118566[/C][C]39846[/C][/ROW]
[ROW][C]3[/C][C]44576.0833333333[/C][C]10445.1370020897[/C][C]39846[/C][/ROW]
[ROW][C]4[/C][C]51422.75[/C][C]14282.4348390538[/C][C]42300[/C][/ROW]
[ROW][C]5[/C][C]75496.3333333333[/C][C]14583.6730149184[/C][C]48581[/C][/ROW]
[ROW][C]6[/C][C]114399.666666667[/C][C]21570.4708986123[/C][C]64811[/C][/ROW]
[ROW][C]7[/C][C]157145[/C][C]22393.6361658234[/C][C]66049[/C][/ROW]
[ROW][C]8[/C][C]186199.333333333[/C][C]17490.2167320286[/C][C]54862[/C][/ROW]
[ROW][C]9[/C][C]213889.833333333[/C][C]16626.212047866[/C][C]57314[/C][/ROW]
[ROW][C]10[/C][C]244925.666666667[/C][C]14416.1864603856[/C][C]48579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210877&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210877&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
167889.510852.339718403432338
247477.666666666711322.818411856639846
344576.083333333310445.137002089739846
451422.7514282.434839053842300
575496.333333333314583.673014918448581
6114399.66666666721570.470898612364811
715714522393.636165823466049
8186199.33333333317490.216732028654862
9213889.83333333316626.21204786657314
10244925.66666666714416.186460385648579






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha12125.2163045756
beta0.027198245319034
S.D.0.0172380618445869
T-STAT1.57780181810723
p-value0.153263129856937

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 12125.2163045756 \tabularnewline
beta & 0.027198245319034 \tabularnewline
S.D. & 0.0172380618445869 \tabularnewline
T-STAT & 1.57780181810723 \tabularnewline
p-value & 0.153263129856937 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210877&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12125.2163045756[/C][/ROW]
[ROW][C]beta[/C][C]0.027198245319034[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0172380618445869[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.57780181810723[/C][/ROW]
[ROW][C]p-value[/C][C]0.153263129856937[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210877&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210877&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)
alpha12125.2163045756
beta0.027198245319034
S.D.0.0172380618445869
T-STAT1.57780181810723
p-value0.153263129856937






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.52730117944094
beta0.267766906246903
S.D.0.109134701061175
T-STAT2.45354505618526
p-value0.0397165412926234
Lambda0.732233093753097

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.52730117944094 \tabularnewline
beta & 0.267766906246903 \tabularnewline
S.D. & 0.109134701061175 \tabularnewline
T-STAT & 2.45354505618526 \tabularnewline
p-value & 0.0397165412926234 \tabularnewline
Lambda & 0.732233093753097 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210877&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.52730117944094[/C][/ROW]
[ROW][C]beta[/C][C]0.267766906246903[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109134701061175[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.45354505618526[/C][/ROW]
[ROW][C]p-value[/C][C]0.0397165412926234[/C][/ROW]
[ROW][C]Lambda[/C][C]0.732233093753097[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210877&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210877&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)
alpha6.52730117944094
beta0.267766906246903
S.D.0.109134701061175
T-STAT2.45354505618526
p-value0.0397165412926234
Lambda0.732233093753097


Figures (Output of Computation)

Input Parameters & R Code

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')