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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 computationTue, 09 Dec 2008 07:32:49 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/09/t1228833592ln3yvs8a16x1uyt.htm/, Retrieved Sat, 25 May 2024 12:39:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31470, Retrieved Sat, 25 May 2024 12:39:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Standard Deviation-Mean Plot] [Step1] [2008-12-09 14:32:49] [a413cf7744efd6bb212437a3916e2f23] [Current]
Feedback Forum
2008-12-14 13:18:24 [Gert-Jan Geudens] [reply] 
Foutieve conclusie. De p-waarde is groter dan 0.05 en dus is de transformatie nutteloos. Als we een punt zouden toevoegen aan de standard-deviation mean plot (bv. linksvanboven), zou dit een vertekend beeld kunnen geven aan onze regressielijn. De transformatie is dus nutteloos. We moeten dan in latere stappen, lambda telkens gelijkstellen aan 1.
2008-12-15 14:26:15 [Jonas Scheltjens] [reply] 
De student heeft hier enkel de link en 2 tabellen gegeven zonder enige degelijke uitleg of verklaring. Aangezien het niet de taak is van de persoon die de assessments doet om deze taak voor de student te maken, verwijs ik dan ook voor de algemene en volledige uitleg voor deze Step naar Step 1 voor de unemployment data, dewelke ik zeer uitgebreid heb besproken en waar alle informatie in staat om deze vraag correct op te lossen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1846,5
2796,3
2895,6
2472,2
2584,4
2630,4
2663,1
3176,2
2856,7
2551,4
3088,7
2628,3
2226,2
3023,6
3077,9
3084,1
2990,3
2949,6
3014,7
3517,7
3121,2
3067,4
3174,6
2676,3
2424
3195,1
3146,6
3506,7
3528,5
3365,1
3153
3843,3
3123,2
3361,1
3481,9
2970,5
2537
3257,6
3301,3
3391,6
2933,6
3283,2
3139,7
3486,4
3202,2
3294,4
3550,3
3279,3
2678,6
3451,4
3977,1
3814,8
3310,5
3971,8
4051,9
4057,6
4391,4
3628,9
4092,2
3822,5

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31470&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31470&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31470&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12682.48333333333340.2415100359081329.7
22993.63333333333307.0891026553971291.5
33258.25353.37376169511419.3
43221.38333333333267.2824649328981013.3
53770.725453.693146450731712.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2682.48333333333 & 340.241510035908 & 1329.7 \tabularnewline
2 & 2993.63333333333 & 307.089102655397 & 1291.5 \tabularnewline
3 & 3258.25 & 353.3737616951 & 1419.3 \tabularnewline
4 & 3221.38333333333 & 267.282464932898 & 1013.3 \tabularnewline
5 & 3770.725 & 453.69314645073 & 1712.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31470&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]2682.48333333333[/C][C]340.241510035908[/C][C]1329.7[/C][/ROW]
[ROW][C]2[/C][C]2993.63333333333[/C][C]307.089102655397[/C][C]1291.5[/C][/ROW]
[ROW][C]3[/C][C]3258.25[/C][C]353.3737616951[/C][C]1419.3[/C][/ROW]
[ROW][C]4[/C][C]3221.38333333333[/C][C]267.282464932898[/C][C]1013.3[/C][/ROW]
[ROW][C]5[/C][C]3770.725[/C][C]453.69314645073[/C][C]1712.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31470&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31470&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
12682.48333333333340.2415100359081329.7
22993.63333333333307.0891026553971291.5
33258.25353.37376169511419.3
43221.38333333333267.2824649328981013.3
53770.725453.693146450731712.8






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-10.1215156948041
beta0.111279336089377
S.D.0.0773587222583548
T-STAT1.4384846703871
p-value0.245879924162917

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -10.1215156948041 \tabularnewline
beta & 0.111279336089377 \tabularnewline
S.D. & 0.0773587222583548 \tabularnewline
T-STAT & 1.4384846703871 \tabularnewline
p-value & 0.245879924162917 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31470&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.1215156948041[/C][/ROW]
[ROW][C]beta[/C][C]0.111279336089377[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0773587222583548[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.4384846703871[/C][/ROW]
[ROW][C]p-value[/C][C]0.245879924162917[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31470&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31470&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)
alpha-10.1215156948041
beta0.111279336089377
S.D.0.0773587222583548
T-STAT1.4384846703871
p-value0.245879924162917






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.02529666795173
beta0.85003216177126
S.D.0.760067791065588
T-STAT1.11836361409230
p-value0.344894045788349
Lambda0.14996783822874

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.02529666795173 \tabularnewline
beta & 0.85003216177126 \tabularnewline
S.D. & 0.760067791065588 \tabularnewline
T-STAT & 1.11836361409230 \tabularnewline
p-value & 0.344894045788349 \tabularnewline
Lambda & 0.14996783822874 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31470&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.02529666795173[/C][/ROW]
[ROW][C]beta[/C][C]0.85003216177126[/C][/ROW]
[ROW][C]S.D.[/C][C]0.760067791065588[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11836361409230[/C][/ROW]
[ROW][C]p-value[/C][C]0.344894045788349[/C][/ROW]
[ROW][C]Lambda[/C][C]0.14996783822874[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31470&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31470&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-1.02529666795173
beta0.85003216177126
S.D.0.760067791065588
T-STAT1.11836361409230
p-value0.344894045788349
Lambda0.14996783822874


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')