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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 computationSun, 04 Dec 2011 14:11:32 -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/2011/Dec/04/t1323025925zajfanawk50i0la.htm/, Retrieved Sun, 05 May 2024 18:24:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=150745, Retrieved Sun, 05 May 2024 18:24:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact99

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Blocked Bootstrap Plot - Central Tendency] [Evolutie gemiddel...] [2011-12-04 18:09:38] [d700a6813b2ef07b7398fe84f8eae4b7]
- RMPD    [Standard Deviation-Mean Plot] [Evolutie gemiddel...] [2011-12-04 19:11:32] [9b00bb73e1719a6b710100764835da33] [Current]
- R P       [Standard Deviation-Mean Plot] [KDGP2W83] [2011-12-11 13:11:58] [d700a6813b2ef07b7398fe84f8eae4b7]
-             [Standard Deviation-Mean Plot] [Evolutie gemiddel...] [2011-12-11 13:44:08] [d700a6813b2ef07b7398fe84f8eae4b7]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10.93
10.92
10.89
10.94
10.98
10.99
11.02
11.04
11.05
11.05
11.02
10.91
11.01
11.02
11.03
11.04
11.06
11.08
11.06
11.06
11.09
11.07
11.06
11.08
11.08
11.08
11.11
11.09
11.08
11.05
11.07
11.06
11.06
11.07
11.02
11.01
11.04
11.02
11.03
11.17
11.19
11.15
11.13
11.06
11.01
11.03
10.99
10.94
11
11.06
11.06
11.05
11.04
11.15
11.2
11.16
11.3
11.23
11.25
11.25
11.12
11.14
11.17
11.25
11.27
11.34
11.39
11.44
11.46
11.49
11.51
11.48
11.49
11.52
11.56
11.58
11.58
11.58
11.6
11.62
11.62
11.64
11.67
11.66
11.72
11.82
11.9
12.04
12.08
12.15
12.19
12.22
12.23
12.25
12.26
12.27
12.34
12.38
12.42
12.43
12.48
12.5
12.5
12.49
12.46
12.45
12.45
12.38
12.42
12.37
12.35
12.35
12.36
12.32
12.32
12.34
12.35
12.34
12.31
12.24

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150745&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150745&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150745&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110.920.02160246899469240.0499999999999989
211.00750.02753785273642990.0599999999999987
311.00750.06652067347825060.140000000000001
411.0250.01290994448735780.0299999999999994
511.0650.009999999999999790.0199999999999996
611.0750.01290994448735780.0299999999999994
711.090.01414213562373060.0299999999999994
811.0650.01290994448735780.0299999999999994
911.040.02943920288775990.0600000000000005
1011.0650.07047458170622020.15
1111.13250.05439056290693540.129999999999999
1210.99250.03862210075418820.0899999999999999
1311.04250.02872281323269040.0600000000000005
1411.13750.06849574196011530.16
1511.25750.02986078811194840.0700000000000003
1611.170.05715476066494090.130000000000001
1711.360.07257180352359090.17
1811.4850.02081665999466090.0499999999999989
1911.53750.04031128874149280.0899999999999999
2011.5950.01914854215512640.0399999999999991
2111.64750.02217355782608370.0500000000000007
2211.870.1351542328847550.319999999999999
2312.160.06055300708194990.140000000000001
2412.25250.0170782512765990.0399999999999991
2512.39250.04112987559751010.0899999999999999
2612.49250.009574271077563180.0199999999999996
2712.4350.03696845502136430.0800000000000001
2812.37250.03304037933599850.0700000000000003
2912.3350.01914854215512640.0399999999999991
3012.310.04966554808583760.109999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10.92 & 0.0216024689946924 & 0.0499999999999989 \tabularnewline
2 & 11.0075 & 0.0275378527364299 & 0.0599999999999987 \tabularnewline
3 & 11.0075 & 0.0665206734782506 & 0.140000000000001 \tabularnewline
4 & 11.025 & 0.0129099444873578 & 0.0299999999999994 \tabularnewline
5 & 11.065 & 0.00999999999999979 & 0.0199999999999996 \tabularnewline
6 & 11.075 & 0.0129099444873578 & 0.0299999999999994 \tabularnewline
7 & 11.09 & 0.0141421356237306 & 0.0299999999999994 \tabularnewline
8 & 11.065 & 0.0129099444873578 & 0.0299999999999994 \tabularnewline
9 & 11.04 & 0.0294392028877599 & 0.0600000000000005 \tabularnewline
10 & 11.065 & 0.0704745817062202 & 0.15 \tabularnewline
11 & 11.1325 & 0.0543905629069354 & 0.129999999999999 \tabularnewline
12 & 10.9925 & 0.0386221007541882 & 0.0899999999999999 \tabularnewline
13 & 11.0425 & 0.0287228132326904 & 0.0600000000000005 \tabularnewline
14 & 11.1375 & 0.0684957419601153 & 0.16 \tabularnewline
15 & 11.2575 & 0.0298607881119484 & 0.0700000000000003 \tabularnewline
16 & 11.17 & 0.0571547606649409 & 0.130000000000001 \tabularnewline
17 & 11.36 & 0.0725718035235909 & 0.17 \tabularnewline
18 & 11.485 & 0.0208166599946609 & 0.0499999999999989 \tabularnewline
19 & 11.5375 & 0.0403112887414928 & 0.0899999999999999 \tabularnewline
20 & 11.595 & 0.0191485421551264 & 0.0399999999999991 \tabularnewline
21 & 11.6475 & 0.0221735578260837 & 0.0500000000000007 \tabularnewline
22 & 11.87 & 0.135154232884755 & 0.319999999999999 \tabularnewline
23 & 12.16 & 0.0605530070819499 & 0.140000000000001 \tabularnewline
24 & 12.2525 & 0.017078251276599 & 0.0399999999999991 \tabularnewline
25 & 12.3925 & 0.0411298755975101 & 0.0899999999999999 \tabularnewline
26 & 12.4925 & 0.00957427107756318 & 0.0199999999999996 \tabularnewline
27 & 12.435 & 0.0369684550213643 & 0.0800000000000001 \tabularnewline
28 & 12.3725 & 0.0330403793359985 & 0.0700000000000003 \tabularnewline
29 & 12.335 & 0.0191485421551264 & 0.0399999999999991 \tabularnewline
30 & 12.31 & 0.0496655480858376 & 0.109999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150745&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]10.92[/C][C]0.0216024689946924[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]2[/C][C]11.0075[/C][C]0.0275378527364299[/C][C]0.0599999999999987[/C][/ROW]
[ROW][C]3[/C][C]11.0075[/C][C]0.0665206734782506[/C][C]0.140000000000001[/C][/ROW]
[ROW][C]4[/C][C]11.025[/C][C]0.0129099444873578[/C][C]0.0299999999999994[/C][/ROW]
[ROW][C]5[/C][C]11.065[/C][C]0.00999999999999979[/C][C]0.0199999999999996[/C][/ROW]
[ROW][C]6[/C][C]11.075[/C][C]0.0129099444873578[/C][C]0.0299999999999994[/C][/ROW]
[ROW][C]7[/C][C]11.09[/C][C]0.0141421356237306[/C][C]0.0299999999999994[/C][/ROW]
[ROW][C]8[/C][C]11.065[/C][C]0.0129099444873578[/C][C]0.0299999999999994[/C][/ROW]
[ROW][C]9[/C][C]11.04[/C][C]0.0294392028877599[/C][C]0.0600000000000005[/C][/ROW]
[ROW][C]10[/C][C]11.065[/C][C]0.0704745817062202[/C][C]0.15[/C][/ROW]
[ROW][C]11[/C][C]11.1325[/C][C]0.0543905629069354[/C][C]0.129999999999999[/C][/ROW]
[ROW][C]12[/C][C]10.9925[/C][C]0.0386221007541882[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]13[/C][C]11.0425[/C][C]0.0287228132326904[/C][C]0.0600000000000005[/C][/ROW]
[ROW][C]14[/C][C]11.1375[/C][C]0.0684957419601153[/C][C]0.16[/C][/ROW]
[ROW][C]15[/C][C]11.2575[/C][C]0.0298607881119484[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]16[/C][C]11.17[/C][C]0.0571547606649409[/C][C]0.130000000000001[/C][/ROW]
[ROW][C]17[/C][C]11.36[/C][C]0.0725718035235909[/C][C]0.17[/C][/ROW]
[ROW][C]18[/C][C]11.485[/C][C]0.0208166599946609[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]19[/C][C]11.5375[/C][C]0.0403112887414928[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]20[/C][C]11.595[/C][C]0.0191485421551264[/C][C]0.0399999999999991[/C][/ROW]
[ROW][C]21[/C][C]11.6475[/C][C]0.0221735578260837[/C][C]0.0500000000000007[/C][/ROW]
[ROW][C]22[/C][C]11.87[/C][C]0.135154232884755[/C][C]0.319999999999999[/C][/ROW]
[ROW][C]23[/C][C]12.16[/C][C]0.0605530070819499[/C][C]0.140000000000001[/C][/ROW]
[ROW][C]24[/C][C]12.2525[/C][C]0.017078251276599[/C][C]0.0399999999999991[/C][/ROW]
[ROW][C]25[/C][C]12.3925[/C][C]0.0411298755975101[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]26[/C][C]12.4925[/C][C]0.00957427107756318[/C][C]0.0199999999999996[/C][/ROW]
[ROW][C]27[/C][C]12.435[/C][C]0.0369684550213643[/C][C]0.0800000000000001[/C][/ROW]
[ROW][C]28[/C][C]12.3725[/C][C]0.0330403793359985[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]29[/C][C]12.335[/C][C]0.0191485421551264[/C][C]0.0399999999999991[/C][/ROW]
[ROW][C]30[/C][C]12.31[/C][C]0.0496655480858376[/C][C]0.109999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150745&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150745&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
110.920.02160246899469240.0499999999999989
211.00750.02753785273642990.0599999999999987
311.00750.06652067347825060.140000000000001
411.0250.01290994448735780.0299999999999994
511.0650.009999999999999790.0199999999999996
611.0750.01290994448735780.0299999999999994
711.090.01414213562373060.0299999999999994
811.0650.01290994448735780.0299999999999994
911.040.02943920288775990.0600000000000005
1011.0650.07047458170622020.15
1111.13250.05439056290693540.129999999999999
1210.99250.03862210075418820.0899999999999999
1311.04250.02872281323269040.0600000000000005
1411.13750.06849574196011530.16
1511.25750.02986078811194840.0700000000000003
1611.170.05715476066494090.130000000000001
1711.360.07257180352359090.17
1811.4850.02081665999466090.0499999999999989
1911.53750.04031128874149280.0899999999999999
2011.5950.01914854215512640.0399999999999991
2111.64750.02217355782608370.0500000000000007
2211.870.1351542328847550.319999999999999
2312.160.06055300708194990.140000000000001
2412.25250.0170782512765990.0399999999999991
2512.39250.04112987559751010.0899999999999999
2612.49250.009574271077563180.0199999999999996
2712.4350.03696845502136430.0800000000000001
2812.37250.03304037933599850.0700000000000003
2912.3350.01914854215512640.0399999999999991
3012.310.04966554808583760.109999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0149179691421215
beta0.00198498239262747
S.D.0.00912568254657948
T-STAT0.2175160468815
p-value0.829383530230911

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0149179691421215 \tabularnewline
beta & 0.00198498239262747 \tabularnewline
S.D. & 0.00912568254657948 \tabularnewline
T-STAT & 0.2175160468815 \tabularnewline
p-value & 0.829383530230911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150745&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0149179691421215[/C][/ROW]
[ROW][C]beta[/C][C]0.00198498239262747[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00912568254657948[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.2175160468815[/C][/ROW]
[ROW][C]p-value[/C][C]0.829383530230911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150745&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150745&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)
alpha0.0149179691421215
beta0.00198498239262747
S.D.0.00912568254657948
T-STAT0.2175160468815
p-value0.829383530230911






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.92251082156761
beta0.584520005560723
S.D.2.66451356263492
T-STAT0.219372126213798
p-value0.827951550052222
Lambda0.415479994439277

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.92251082156761 \tabularnewline
beta & 0.584520005560723 \tabularnewline
S.D. & 2.66451356263492 \tabularnewline
T-STAT & 0.219372126213798 \tabularnewline
p-value & 0.827951550052222 \tabularnewline
Lambda & 0.415479994439277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150745&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.92251082156761[/C][/ROW]
[ROW][C]beta[/C][C]0.584520005560723[/C][/ROW]
[ROW][C]S.D.[/C][C]2.66451356263492[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.219372126213798[/C][/ROW]
[ROW][C]p-value[/C][C]0.827951550052222[/C][/ROW]
[ROW][C]Lambda[/C][C]0.415479994439277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150745&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150745&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)
alpha-4.92251082156761
beta0.584520005560723
S.D.2.66451356263492
T-STAT0.219372126213798
p-value0.827951550052222
Lambda0.415479994439277


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')