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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, 03 Jun 2010 09:13:50 +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/Jun/03/t1275556548v6k68wdy4wcuvfq.htm/, Retrieved Sun, 05 May 2024 15:39:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77339, Retrieved Sun, 05 May 2024 15:39:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W82
Estimated Impact192

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] [] [2010-06-03 09:13:50] [850dbf9e683f79d78a1e8310559edb6e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
306
303
344
254
309
310
379
294
356
318
405
545
268
243
273
273
236
222
302
285
309
322
362
471
198
253
173
186
185
105
228
214
189
270
277
378
185
182
258
179
197
168
250
211
260
234
305
347
203
217
227
242
185
175
252
319
202
254
336
431
150
280
187
279
193
227
225
205
259
254
275
394
159
230
188
195
189
220
274

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77339&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77339&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77339&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 time4 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1343.58333333333375.2395668796839291
2297.16666666666767.213139047407249
3221.33333333333368.1846868083407273
4231.33333333333355.281648004203179
5253.58333333333374.3633075861444256
624462.6418390534633244

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 343.583333333333 & 75.2395668796839 & 291 \tabularnewline
2 & 297.166666666667 & 67.213139047407 & 249 \tabularnewline
3 & 221.333333333333 & 68.1846868083407 & 273 \tabularnewline
4 & 231.333333333333 & 55.281648004203 & 179 \tabularnewline
5 & 253.583333333333 & 74.3633075861444 & 256 \tabularnewline
6 & 244 & 62.6418390534633 & 244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77339&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]343.583333333333[/C][C]75.2395668796839[/C][C]291[/C][/ROW]
[ROW][C]2[/C][C]297.166666666667[/C][C]67.213139047407[/C][C]249[/C][/ROW]
[ROW][C]3[/C][C]221.333333333333[/C][C]68.1846868083407[/C][C]273[/C][/ROW]
[ROW][C]4[/C][C]231.333333333333[/C][C]55.281648004203[/C][C]179[/C][/ROW]
[ROW][C]5[/C][C]253.583333333333[/C][C]74.3633075861444[/C][C]256[/C][/ROW]
[ROW][C]6[/C][C]244[/C][C]62.6418390534633[/C][C]244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77339&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77339&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
1343.58333333333375.2395668796839291
2297.16666666666767.213139047407249
3221.33333333333368.1846868083407273
4231.33333333333355.281648004203179
5253.58333333333374.3633075861444256
624462.6418390534633244






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha42.5414360381878
beta0.0928193407606007
S.D.0.0656393141609665
T-STAT1.41408151421237
p-value0.230235582834280

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 42.5414360381878 \tabularnewline
beta & 0.0928193407606007 \tabularnewline
S.D. & 0.0656393141609665 \tabularnewline
T-STAT & 1.41408151421237 \tabularnewline
p-value & 0.230235582834280 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77339&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]42.5414360381878[/C][/ROW]
[ROW][C]beta[/C][C]0.0928193407606007[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0656393141609665[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.41408151421237[/C][/ROW]
[ROW][C]p-value[/C][C]0.230235582834280[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77339&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77339&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)
alpha42.5414360381878
beta0.0928193407606007
S.D.0.0656393141609665
T-STAT1.41408151421237
p-value0.230235582834280






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.03702057655058
beta0.388728992135964
S.D.0.284051449568799
T-STAT1.36851613581296
p-value0.24297661714381
Lambda0.611271007864036

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.03702057655058 \tabularnewline
beta & 0.388728992135964 \tabularnewline
S.D. & 0.284051449568799 \tabularnewline
T-STAT & 1.36851613581296 \tabularnewline
p-value & 0.24297661714381 \tabularnewline
Lambda & 0.611271007864036 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77339&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.03702057655058[/C][/ROW]
[ROW][C]beta[/C][C]0.388728992135964[/C][/ROW]
[ROW][C]S.D.[/C][C]0.284051449568799[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.36851613581296[/C][/ROW]
[ROW][C]p-value[/C][C]0.24297661714381[/C][/ROW]
[ROW][C]Lambda[/C][C]0.611271007864036[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77339&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77339&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)
alpha2.03702057655058
beta0.388728992135964
S.D.0.284051449568799
T-STAT1.36851613581296
p-value0.24297661714381
Lambda0.611271007864036


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')