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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 computationWed, 10 Dec 2014 12:28:56 +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/2014/Dec/10/t1418214564tx5gc66qmmqr7hr.htm/, Retrieved Tue, 10 Feb 2026 08:36:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265022, Retrieved Tue, 10 Feb 2026 08:36:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact417

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]
- R PD  [Survey Scores] [] [2011-10-18 12:18:26] [b98453cac15ba1066b407e146608df68]
- RM      [Survey Scores] [WS3 Question 1] [2014-10-15 11:54:25] [f13ab2b9cdb9c17a0cf473fdf5cac3ab]
- RM D        [Survey Scores] [paper] [2014-12-10 12:28:56] [f37066d0c2d3549c99d3204e671bd762] [Current]
-    D          [Survey Scores] [paper] [2014-12-10 13:14:31] [074b0dbc8d3b700fa15927150828e345]
-    D          [Survey Scores] [paper] [2014-12-10 13:16:41] [074b0dbc8d3b700fa15927150828e345]
-    D          [Survey Scores] [paper] [2014-12-10 13:17:47] [074b0dbc8d3b700fa15927150828e345]
-    D          [Survey Scores] [paper] [2014-12-10 13:18:48] [074b0dbc8d3b700fa15927150828e345]
-    D          [Survey Scores] [paper] [2014-12-10 13:19:51] [074b0dbc8d3b700fa15927150828e345]
-   PD          [Survey Scores] [paper] [2014-12-10 13:20:52] [074b0dbc8d3b700fa15927150828e345]
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Dataset

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

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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265022&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265022&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265022&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' @ jenkins.wessa.net






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)
10.9297380.77189270.75
20.79287590.66191390.66
31323370.79207240.79
41.35410220.9230170.86

\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 & 0.9 & 297 & 38 & 0.77 & 189 & 27 & 0.75 \tabularnewline
2 & 0.79 & 287 & 59 & 0.66 & 191 & 39 & 0.66 \tabularnewline
3 & 1 & 323 & 37 & 0.79 & 207 & 24 & 0.79 \tabularnewline
4 & 1.35 & 410 & 22 & 0.9 & 230 & 17 & 0.86 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265022&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]0.9[/C][C]297[/C][C]38[/C][C]0.77[/C][C]189[/C][C]27[/C][C]0.75[/C][/ROW]
[ROW][C]2[/C][C]0.79[/C][C]287[/C][C]59[/C][C]0.66[/C][C]191[/C][C]39[/C][C]0.66[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]323[/C][C]37[/C][C]0.79[/C][C]207[/C][C]24[/C][C]0.79[/C][/ROW]
[ROW][C]4[/C][C]1.35[/C][C]410[/C][C]22[/C][C]0.9[/C][C]230[/C][C]17[/C][C]0.86[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265022&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265022&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)
10.9297380.77189270.75
20.79287590.66191390.66
31323370.79207240.79
41.35410220.9230170.86






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.954 (0.046)0.936 (0.064)
(Ps-Ns)/(Ps+Ns)0.954 (0.046)1 (0)0.991 (0.009)
(Pc-Nc)/(Pc+Nc)0.936 (0.064)0.991 (0.009)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) & 0.954 (0.046) & 0.936 (0.064) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.954 (0.046) & 1 (0) & 0.991 (0.009) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.936 (0.064) & 0.991 (0.009) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265022&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]0.954 (0.046)[/C][C]0.936 (0.064)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.954 (0.046)[/C][C]1 (0)[/C][C]0.991 (0.009)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.936 (0.064)[/C][C]0.991 (0.009)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265022&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265022&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)0.954 (0.046)0.936 (0.064)
(Ps-Ns)/(Ps+Ns)0.954 (0.046)1 (0)0.991 (0.009)
(Pc-Nc)/(Pc+Nc)0.936 (0.064)0.991 (0.009)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=265022&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=265022&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265022&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')