FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSat, 15 Dec 2012 09:45:17 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/15/t1355582733231g0zt6x67a8fd.htm/, Retrieved Tue, 30 Apr 2024 20:05:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199976, Retrieved Tue, 30 Apr 2024 20:05:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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]
- R  D    [Standard Deviation-Mean Plot] [] [2012-11-24 14:45:44] [ed1b7ed66647a67413eed9d47e0cd105]
-   PD        [Standard Deviation-Mean Plot] [] [2012-12-15 14:45:17] [7d61013405aa85534cb0146e7095f1e4] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7116
6927
6731
6850
6766
6979
7149
7067
7170
7237
7240
7645
7678
7491
7816
7631
8395
8578
8950
9450
9501
10083
10544
11299
12049
12860
13389
13796
14505
14727
14646
14861
15012
15421
15227
15124
14953
15039
15128
15221
14876
14517
14609
14735
14574
14636
15104
14393
13919
13751
13628
13792
13892
14024
13908
13920
13897
13759
13323
13097
12758
12806
12673
12500
12720
12749
12794
12544
12088
12258

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'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199976&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199976&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199976&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17073.08333333333250.478254666161914
28951.333333333331247.349796629443808
314301.41666666671052.494651969433372
414815.4166666667273.879687697597828
513742.5273.70637884087927

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7073.08333333333 & 250.478254666161 & 914 \tabularnewline
2 & 8951.33333333333 & 1247.34979662944 & 3808 \tabularnewline
3 & 14301.4166666667 & 1052.49465196943 & 3372 \tabularnewline
4 & 14815.4166666667 & 273.879687697597 & 828 \tabularnewline
5 & 13742.5 & 273.70637884087 & 927 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199976&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]7073.08333333333[/C][C]250.478254666161[/C][C]914[/C][/ROW]
[ROW][C]2[/C][C]8951.33333333333[/C][C]1247.34979662944[/C][C]3808[/C][/ROW]
[ROW][C]3[/C][C]14301.4166666667[/C][C]1052.49465196943[/C][C]3372[/C][/ROW]
[ROW][C]4[/C][C]14815.4166666667[/C][C]273.879687697597[/C][C]828[/C][/ROW]
[ROW][C]5[/C][C]13742.5[/C][C]273.70637884087[/C][C]927[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199976&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199976&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
17073.08333333333250.478254666161914
28951.333333333331247.349796629443808
314301.41666666671052.494651969433372
414815.4166666667273.879687697597828
513742.5273.70637884087927






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha779.913781107917
beta-0.0136142846835687
S.D.0.0798223011885394
T-STAT-0.170557406650202
p-value0.87542584809517

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 779.913781107917 \tabularnewline
beta & -0.0136142846835687 \tabularnewline
S.D. & 0.0798223011885394 \tabularnewline
T-STAT & -0.170557406650202 \tabularnewline
p-value & 0.87542584809517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199976&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]779.913781107917[/C][/ROW]
[ROW][C]beta[/C][C]-0.0136142846835687[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0798223011885394[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.170557406650202[/C][/ROW]
[ROW][C]p-value[/C][C]0.87542584809517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199976&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199976&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)
alpha779.913781107917
beta-0.0136142846835687
S.D.0.0798223011885394
T-STAT-0.170557406650202
p-value0.87542584809517






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.05605521421171
beta0.0119051725375675
S.D.1.39698892980483
T-STAT0.00852202353473966
p-value0.99373551733817
Lambda0.988094827462432

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.05605521421171 \tabularnewline
beta & 0.0119051725375675 \tabularnewline
S.D. & 1.39698892980483 \tabularnewline
T-STAT & 0.00852202353473966 \tabularnewline
p-value & 0.99373551733817 \tabularnewline
Lambda & 0.988094827462432 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199976&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.05605521421171[/C][/ROW]
[ROW][C]beta[/C][C]0.0119051725375675[/C][/ROW]
[ROW][C]S.D.[/C][C]1.39698892980483[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.00852202353473966[/C][/ROW]
[ROW][C]p-value[/C][C]0.99373551733817[/C][/ROW]
[ROW][C]Lambda[/C][C]0.988094827462432[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199976&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199976&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)
alpha6.05605521421171
beta0.0119051725375675
S.D.1.39698892980483
T-STAT0.00852202353473966
p-value0.99373551733817
Lambda0.988094827462432


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')