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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, 09 Dec 2014 13:13:01 +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/09/t1418130806fhtla3guela7i7t.htm/, Retrieved Thu, 31 Oct 2024 23:11:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264568, Retrieved Thu, 31 Oct 2024 23:11:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Reddy Moores Boxp...] [2010-10-12 16:37:57] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Boxplot and Trimmed Means] [Reddy-Moores Plac...] [2010-10-13 09:46:26] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD    [Notched Boxplots] [] [2010-10-15 11:13:23] [b98453cac15ba1066b407e146608df68]
- RMPD        [Survey Scores] [i2_KWALITATIEF] [2014-12-09 13:13:01] [abae100319030711995379e8f3c2e274] [Current]
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Dataseries X:
2 2 2 2
4 4 5 5
3 3 3 3
7 6 6 5
3 4 5 4
5 5 5 4
5 5 1 5
4 4 4 3
7 7 7 7
5 5 6 5
3 5 5 5
6 5 6 5
2 5 6 6
5 5 6 6
5 6 7 7
4 5 6 5
4 4 5 3
5 5 4 5
5 4 4 5
6 7 6 7
6 6 5 7
5 5 5 5
5 4 5 5
3 5 6 5
6 6 5 6
5 5 4 4
4 5 3 4
4 5 4 5
4 6 6 5
4 5 5 6
3 5 5 2
5 5 5 4
4 5 6 4
2 1 2 2
3 5 6 6
5 5 5 5
5 6 3 5
5 4 6 4
5 5 5 5
4 3 4 7
4 3 5 2
3 4 5 5
4 4 4 5
2 2 2 2
2 3 2 2
5 5 6 6
5 5 5 5
5 6 5 4
4 6 6 6
6 5 6 5
5 5 6 6
2 4 5 5
4 2 3 5
6 6 6 6
5 5 6 5
5 5 5 5
2 6 6 6
3 6 5 4
3 5 3 3
5 5 5 4
7 6 6 5
4 3 6 6
2 3 6 5
2 4 5 5
4 5 5 2
4 4 3 3
5 5 6 6
4 4 7 6
4 5 4 2
3 3 5 3
4 3 5 3
3 2 4 5
6 5 4 5
6 5 5 5
2 2 4 6
2 4 5 5
4 3 3 3
7 6 7 6
3 3 5 2
4 4 5 5
4 4 3 4
4 4 5 5
6 5 6 4
3 4 5 5
5 4 6 3
5 5 5 5
4 5 4 5
6 7 6 6
4 5 5 6
4 4 6 5
4 4 5 5
3 3 3 3
4 5 7 6
2 5 4 5
4 5 5 4
5 6 6 6
4 5 6 5
4 5 6 5
4 4 4 4
6 6 4 6
4 5 5 5
5 7 6 5
1 2 2 1
4 4 6 5
5 6 6 7
5 4 5 5
2 4 4 5
3 5 6 4
5 4 4 5
5 6 6 5
5 6 6 6
1 6 5 6
4 5 4 4
2 2 1 1
3 5 7 7
5 5 5 5
3 4 5 4
4 6 3 3
5 4 4 4
6 6 4 4
5 6 5 7
5 4 4 5
5 3 2 3
6 6 5 5
5 5 5 5
5 5 5 5
2 4 3 4
4 7 4 1
7 7 6 5
4 5 3 4
2 4 5 4
5 5 4 5
6 5 4 4
6 6 6 6
2 2 2 3
5 6 5 6
3 4 4 4
4 6 6 6
5 5 6 6
6 6 5 7
3 2 3 4
2 6 7 6
6 6 6 7
7 7 6 6
5 5 6 5
3 4 3 4
7 7 7 7
5 5 6 5
5 5 3 3
4 3 4 5
6 7 6 6
4 6 5 6
6 5 6 5
3 3 1 2
5 5 5 5
4 6 5 4
7 7 3 7
4 6 6 6
5 5 6 6
1 4 2 5
4 3 5 5
4 5 4 5
2 2 5 1
5 6 6 5
6 7 6 5
3 6 6 3
4 5 4 5
6 5 6 6
4 6 6 5
5 6 5 5
7 7 7 7
4 5 4 4
4 5 6 6
5 5 6 5
5 5 5 5
4 5 4 5
3 4 5 5
1 2 2 2
4 5 5 3
4 4 2 4
4 5 5 4
5 4 2 3
5 6 6 6
5 5 5 5
2 3 5 4
4 6 2 5
6 6 5 4
6 6 6 5
6 6 6 6
4 6 6 5
3 4 4 3
6 6 6 6
3 3 5 5
6 6 4 5
1 4 2 1
5 3 5 4
3 5 6 4
4 4 5 4
4 2 5 5
5 5 6 6
4 5 6 2
5 6 5 5
5 4 6 5
5 5 4 6
3 5 6 5
2 1 1 4
5 3 5 6
2 4 2 3
3 4 3 3
3 5 5 5
5 5 5 4
6 6 6 5
4 4 6 6
5 7 5 5
4 5 5 5
3 4 5 4
3 2 3 3
6 5 5 5
3 3 4 4
5 6 5 5
5 5 4 6
5 5 6 5
4 5 5 6
4 4 5 6
5 5 4 5
4 4 5 5
4 5 6 5
5 5 5 6
5 6 6 5
4 6 4 5
6 6 6 5
4 3 3 6
5 6 6 6
3 5 5 5
5 6 6 6
5 5 5 5
5 5 5 5
6 7 5 5
2 7 2 2
3 6 6 6
7 7 7 5
2 6 5 5
4 6 5 4
5 6 3 4
3 6 6 3
6 6 3 4
4 3 3 3
2 3 2 3
5 6 4 6
7 6 6 5
6 5 4 6
6 6 6 5
3 5 5 5
2 3 5 1
4 5 4 3
6 4 4 6
4 5 5 6
6 7 7 6
3 6 7 5
2 4 2 4
3 5 3 4
3 4 6 5
4 3 3 4
4 5 4 5
2 5 4 5
6 5 5 3
2 3 1 1
6 1 7 7
6 6 6 6
5 5 6 5
5 5 5 5
3 7 5 7
4 5 4 4
4 5 6 4
5 5 5 5
3 5 4 4
5 5 5 5
3 5 4 4




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=264568&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=264568&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264568&T=0

As an alternative you can also use a 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)
10.261871150.24127760.25
20.81285610.65186420.63
30.79293730.6186460.6
40.7268730.57183460.6

\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 & 0.26 & 187 & 115 & 0.24 & 127 & 76 & 0.25 \tabularnewline
2 & 0.81 & 285 & 61 & 0.65 & 186 & 42 & 0.63 \tabularnewline
3 & 0.79 & 293 & 73 & 0.6 & 186 & 46 & 0.6 \tabularnewline
4 & 0.7 & 268 & 73 & 0.57 & 183 & 46 & 0.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264568&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]0.26[/C][C]187[/C][C]115[/C][C]0.24[/C][C]127[/C][C]76[/C][C]0.25[/C][/ROW]
[ROW][C]2[/C][C]0.81[/C][C]285[/C][C]61[/C][C]0.65[/C][C]186[/C][C]42[/C][C]0.63[/C][/ROW]
[ROW][C]3[/C][C]0.79[/C][C]293[/C][C]73[/C][C]0.6[/C][C]186[/C][C]46[/C][C]0.6[/C][/ROW]
[ROW][C]4[/C][C]0.7[/C][C]268[/C][C]73[/C][C]0.57[/C][C]183[/C][C]46[/C][C]0.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264568&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264568&T=1

As an alternative you can also use a 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)
10.261871150.24127760.25
20.81285610.65186420.63
30.79293730.6186460.6
40.7268730.57183460.6







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.996 (0.004)0.989 (0.011)
(Ps-Ns)/(Ps+Ns)0.996 (0.004)1 (0)0.994 (0.006)
(Pc-Nc)/(Pc+Nc)0.989 (0.011)0.994 (0.006)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) & 0.996 (0.004) & 0.989 (0.011) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.996 (0.004) & 1 (0) & 0.994 (0.006) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.989 (0.011) & 0.994 (0.006) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264568&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]0.996 (0.004)[/C][C]0.989 (0.011)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.996 (0.004)[/C][C]1 (0)[/C][C]0.994 (0.006)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.989 (0.011)[/C][C]0.994 (0.006)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264568&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264568&T=2

As an alternative you can also use a 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)0.996 (0.004)0.989 (0.011)
(Ps-Ns)/(Ps+Ns)0.996 (0.004)1 (0)0.994 (0.006)
(Pc-Nc)/(Pc+Nc)0.989 (0.011)0.994 (0.006)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)0.913 (0.071)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)0.913 (0.071)
(Pc-Nc)/(Pc+Nc)0.913 (0.071)0.913 (0.071)1 (0.056)

\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) & 0.913 (0.071) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.083) & 1 (0.083) & 0.913 (0.071) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.913 (0.071) & 0.913 (0.071) & 1 (0.056) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264568&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]0.913 (0.071)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]0.913 (0.071)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.913 (0.071)[/C][C]0.913 (0.071)[/C][C]1 (0.056)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264568&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264568&T=3

As an alternative you can also use a 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)0.913 (0.071)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)0.913 (0.071)
(Pc-Nc)/(Pc+Nc)0.913 (0.071)0.913 (0.071)1 (0.056)



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')