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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationTue, 19 Oct 2010 14:30:20 +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/Oct/19/t1287498564qy1hebwmeosjxpa.htm/, Retrieved Mon, 29 Apr 2024 05:12:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=86527, Retrieved Mon, 29 Apr 2024 05:12:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
F   PD    [Survey Scores] [] [2010-10-19 14:30:20] [a7dcbcc9dd9573c89c41df6a7f8b5a0d] [Current]
Feedback Forum
2010-10-20 17:25:23 [] [reply] 
Men kon ook nog kijken naar de waarden van het gemiddelde tov (Ps-Ns)/(Ps+Ns)tov (Pc-Nc)/(Pc+Nc)als deze wat gelijk lopen. We zien dat bij deze student het gemiddelde respectievelijk veel hoger ligt dan de getallen in de twee andere tabellen. Een extra opmerking is dat in de laatste tabel men kan kijken of er sprake is van rang correlatie.
2010-10-23 10:28:54 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
De student heeft de software hier op een correcte manier gebruikt, maar de resultaten verkeerd geïnterpreteerd. Men ziet hier inderdaad een hoge correlatie, maar dit heeft niks te maken met het aantal positieve antwoorden.

Het ging er in deze eerste vraag eigenlijk om te bepalen of men al dan niet met het rekenkundige gemiddelde mag werken. De hoge correlatie wijst hier op het feit dat de drie berekeningsmethodes (min of meer) aan elkaar kunnen worden gelijkgesteld en dat men in dit geval het rekenkundige gemiddelde mag gebruiken voor verdere berekeningen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7	7	4	5
6	6	6	6
6	6	5	5
5	6	4	5
6	6	6	6
7	7	6	7
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7	6	5	6
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4	7	7	6
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6	7	7	7
6	6	6	5
4	7	6	7
7	7	7	7
7	7	7	6
6	7	6	6
3	5	5	6
7	4	7	6
5	6	5	4
7	7	7	7
6	7	6	7
5	7	6	5
5	7	6	5
6	6	2	6
5	2	2	2
6	6	5	7
6	7	6	6
5	6	6	6
4	4	4	6
5	5	4	6
4	5	5	6
6	6	6	6
6	7	5	5
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7	6	7	6
7	7	5	7
5	6	6	6
6	5	5	6
6	6	6	6
3	7	5	6
6	5	4	5
5	6	5	6
4	5	6	5
6	6	6	7
6	6	3	5
6	6	4	6
5	7	6	5
6	6	6	7
5	6	5	7
7	5	5	6
6	5	5	6
6	6	6	6
7	7	6	5
4	5	6	6
3	4	4	1
4	6	3	4
4	6	5	5
5	7	5	6
4	5	7	7
6	5	5	4
7	7	7	7
6	6	6	6
6	7	6	5
6	6	6	6
6	6	6	6
7	7	7	7
6	7	6	6
6	6	5	4
6	6	7	6
7	6	6	6
5	4	4	5
4	4	4	5
7	7	6	6
7	7	7	7
6	4	6	5
7	7	6	7
6	6	5	5
5	6	5	5
7	6	5	7
6	6	5	5
5	7	6	5
6	6	7	7
5	4	5	5
7	7	7	4
6	6	3	6
2	2	4	5
5	6	6	7
7	6	7	5
7	6	7	6
7	6	6	6
7	7	7	4
6	6	4	6
5	6	5	5
6	6	5	6
6	6	7	6
5	7	6	6
7	7	3	4
5	5	5	6
6	6	6	7
5	7	5	5
5	5	5	5
5	5	5	5
5	6	5	7
7	7	7	7
6	6	6	5
7	7	7	7
6	6	6	6
5	5	4	4
5	5	5	5
7	7	7	7
6	5	5	5
5	6	6	4
7	7	5	6
4	6	2	7
3	6	4	5
7	4	5	5
5	6	5	6
6	5	6	7
4	4	4	3
7	7	7	7
7	7	6	6
5	6	6	6
7	7	6	6
3	6	5	6
6	5	5	6
5	5	5	5
5	6	6	6
6	6	4	6
5	7	6	6
6	6	5	6
6	5	5	6
7	7	5	7
5	5	6	7
7	7	7	6
6	5	6	6
6	5	5	5
7	7	6	6
7	4	6	6
5	6	4	6
7	7	6	7
5	5	4	5
6	5	6	6
7	6	6	6
6	5	6	6
5	6	5	6
6	7	5	4
7	7	5	6
6	7	6	6
7	7	7	7
7	7	7	7
6	4	4	6
6	7	6	6
4	7	4	4
7	6	7	5
6	6	4	6
4	5	4	5
5	5	5	5

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86527&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86527&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86527&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'Gwilym Jenkins' @ 72.249.127.135






Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.7729470.9514260.92
21.9932640.9814920.97
31.49252100.9213470.9
41.7829560.9614830.96

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & 1.77 & 294 & 7 & 0.95 & 142 & 6 & 0.92 \tabularnewline
2 & 1.99 & 326 & 4 & 0.98 & 149 & 2 & 0.97 \tabularnewline
3 & 1.49 & 252 & 10 & 0.92 & 134 & 7 & 0.9 \tabularnewline
4 & 1.78 & 295 & 6 & 0.96 & 148 & 3 & 0.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86527&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]1.77[/C][C]294[/C][C]7[/C][C]0.95[/C][C]142[/C][C]6[/C][C]0.92[/C][/ROW]
[ROW][C]2[/C][C]1.99[/C][C]326[/C][C]4[/C][C]0.98[/C][C]149[/C][C]2[/C][C]0.97[/C][/ROW]
[ROW][C]3[/C][C]1.49[/C][C]252[/C][C]10[/C][C]0.92[/C][C]134[/C][C]7[/C][C]0.9[/C][/ROW]
[ROW][C]4[/C][C]1.78[/C][C]295[/C][C]6[/C][C]0.96[/C][C]148[/C][C]3[/C][C]0.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86527&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86527&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:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.7729470.9514260.92
21.9932640.9814920.97
31.49252100.9213470.9
41.7829560.9614830.96






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.989 (0.011)0.879 (0.121)
(Ps-Ns)/(Ps+Ns)0.989 (0.011)1 (0)0.938 (0.062)
(Pc-Nc)/(Pc+Nc)0.879 (0.121)0.938 (0.062)1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.989 (0.011) & 0.879 (0.121) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.989 (0.011) & 1 (0) & 0.938 (0.062) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.879 (0.121) & 0.938 (0.062) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86527&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.989 (0.011)[/C][C]0.879 (0.121)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.989 (0.011)[/C][C]1 (0)[/C][C]0.938 (0.062)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.879 (0.121)[/C][C]0.938 (0.062)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86527&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86527&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:

Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.989 (0.011)0.879 (0.121)
(Ps-Ns)/(Ps+Ns)0.989 (0.011)1 (0)0.938 (0.062)
(Pc-Nc)/(Pc+Nc)0.879 (0.121)0.938 (0.062)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86527&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86527&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86527&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:

Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 6 7 ;
Parameters (R input):
par1 = 1 2 3 4 5 6 7 ;
R code (references can be found in the software module):
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
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,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
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,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')