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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 computationSat, 13 Dec 2014 09:59:49 +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/13/t1418464817jttn6adx630j774.htm/, Retrieved Thu, 16 May 2024 18:44:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266927, Retrieved Thu, 16 May 2024 18:44:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

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]
- RMP   [Survey Scores] [] [2014-10-09 22:08:50] [32b17a345b130fdf5cc88718ed94a974]
-    D    [Survey Scores] [P IM kwal-kwan] [2014-12-10 19:22:20] [46c7ebd23dbdec306a09830d8b7528e7]
-    D      [Survey Scores] [P IM2 kwal-kwan] [2014-12-12 18:04:48] [46c7ebd23dbdec306a09830d8b7528e7]
-    D        [Survey Scores] [p IM2 kwal-kwan] [2014-12-13 09:43:47] [46c7ebd23dbdec306a09830d8b7528e7]
-    D            [Survey Scores] [P EM1 kwan kwal] [2014-12-13 09:59:49] [9772ee27deeac3d50cc1fb84835cd7d6] [Current]
-    D              [Survey Scores] [P EM2 kwan kwal] [2014-12-13 10:15:42] [46c7ebd23dbdec306a09830d8b7528e7]
-    D                [Survey Scores] [P EM3 kwan kwal] [2014-12-13 10:39:45] [46c7ebd23dbdec306a09830d8b7528e7]
-    D                  [Survey Scores] [P AM kwan kwal] [2014-12-13 10:59:17] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Cronbach Alpha] [P IM1 cronbach] [2014-12-13 11:46:03] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Cronbach Alpha] [P IM2 cronbach] [2014-12-13 11:52:28] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Cronbach Alpha] [P IM3 cronbach] [2014-12-13 12:18:09] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Cronbach Alpha] [P EM1 cronbach] [2014-12-13 12:35:28] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Cronbach Alpha] [P EM2 cronbach] [2014-12-13 12:38:02] [46c7ebd23dbdec306a09830d8b7528e7]
- RMP                   [Cronbach Alpha] [P EM3 cronbach] [2014-12-13 12:40:13] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Cronbach Alpha] [P AM cronbach] [2014-12-13 12:45:08] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [P boxplots alg] [2014-12-13 13:28:53] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [P Boxplots geslacht] [2014-12-13 15:12:20] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [P boxplots studie] [2014-12-13 16:03:12] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [P boxplots jaar] [2014-12-13 16:09:50] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [P boxplotsgeslacht] [2014-12-13 16:23:55] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [P boxplotsstudie] [2014-12-13 16:25:50] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD                  [Notched Boxplots] [p boxplotsjaar] [2014-12-13 16:29:14] [46c7ebd23dbdec306a09830d8b7528e7]
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Dataset

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

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=266927&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=266927&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266927&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






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)
11.76523180.93246140.89
21.86545120.9626180.94
31.49445170.93241150.88
41.8553870.9726740.97

\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 & 1.76 & 523 & 18 & 0.93 & 246 & 14 & 0.89 \tabularnewline
2 & 1.86 & 545 & 12 & 0.96 & 261 & 8 & 0.94 \tabularnewline
3 & 1.49 & 445 & 17 & 0.93 & 241 & 15 & 0.88 \tabularnewline
4 & 1.85 & 538 & 7 & 0.97 & 267 & 4 & 0.97 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266927&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]1.76[/C][C]523[/C][C]18[/C][C]0.93[/C][C]246[/C][C]14[/C][C]0.89[/C][/ROW]
[ROW][C]2[/C][C]1.86[/C][C]545[/C][C]12[/C][C]0.96[/C][C]261[/C][C]8[/C][C]0.94[/C][/ROW]
[ROW][C]3[/C][C]1.49[/C][C]445[/C][C]17[/C][C]0.93[/C][C]241[/C][C]15[/C][C]0.88[/C][/ROW]
[ROW][C]4[/C][C]1.85[/C][C]538[/C][C]7[/C][C]0.97[/C][C]267[/C][C]4[/C][C]0.97[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266927&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266927&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)
11.76523180.93246140.89
21.86545120.9626180.94
31.49445170.93241150.88
41.8553870.9726740.97






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.749 (0.251)0.787 (0.213)
(Ps-Ns)/(Ps+Ns)0.749 (0.251)1 (0)0.991 (0.009)
(Pc-Nc)/(Pc+Nc)0.787 (0.213)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) & 0.749 (0.251) & 0.787 (0.213) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.749 (0.251) & 1 (0) & 0.991 (0.009) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.787 (0.213) & 0.991 (0.009) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266927&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]0.749 (0.251)[/C][C]0.787 (0.213)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.749 (0.251)[/C][C]1 (0)[/C][C]0.991 (0.009)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.787 (0.213)[/C][C]0.991 (0.009)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266927&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266927&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)0.749 (0.251)0.787 (0.213)
(Ps-Ns)/(Ps+Ns)0.749 (0.251)1 (0)0.991 (0.009)
(Pc-Nc)/(Pc+Nc)0.787 (0.213)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)0.548 (0.279)0.667 (0.333)
(Ps-Ns)/(Ps+Ns)0.548 (0.279)1 (0.056)0.913 (0.071)
(Pc-Nc)/(Pc+Nc)0.667 (0.333)0.913 (0.071)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) & 0.548 (0.279) & 0.667 (0.333) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.548 (0.279) & 1 (0.056) & 0.913 (0.071) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.667 (0.333) & 0.913 (0.071) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266927&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]0.548 (0.279)[/C][C]0.667 (0.333)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.548 (0.279)[/C][C]1 (0.056)[/C][C]0.913 (0.071)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.667 (0.333)[/C][C]0.913 (0.071)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266927&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266927&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)0.548 (0.279)0.667 (0.333)
(Ps-Ns)/(Ps+Ns)0.548 (0.279)1 (0.056)0.913 (0.071)
(Pc-Nc)/(Pc+Nc)0.667 (0.333)0.913 (0.071)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')