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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 computationSun, 20 Oct 2013 12:27:07 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/20/t1382286462j8cehql5b9xr3eh.htm/, Retrieved Sat, 27 Apr 2024 20:11:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=217109, Retrieved Sat, 27 Apr 2024 20:11:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86

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] [WS 3: Vraag 1 - E2] [2013-10-20 16:27:07] [0d4b5c001fcd12491258e86d922016e4] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217109&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217109&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217109&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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)
12.845630.9915230.96
21.38251270.81119200.71
31.86316140.92135120.84
42.5241570.9715050.94

\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 & 2.8 & 456 & 3 & 0.99 & 152 & 3 & 0.96 \tabularnewline
2 & 1.38 & 251 & 27 & 0.81 & 119 & 20 & 0.71 \tabularnewline
3 & 1.86 & 316 & 14 & 0.92 & 135 & 12 & 0.84 \tabularnewline
4 & 2.52 & 415 & 7 & 0.97 & 150 & 5 & 0.94 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217109&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]2.8[/C][C]456[/C][C]3[/C][C]0.99[/C][C]152[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]2[/C][C]1.38[/C][C]251[/C][C]27[/C][C]0.81[/C][C]119[/C][C]20[/C][C]0.71[/C][/ROW]
[ROW][C]3[/C][C]1.86[/C][C]316[/C][C]14[/C][C]0.92[/C][C]135[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]4[/C][C]2.52[/C][C]415[/C][C]7[/C][C]0.97[/C][C]150[/C][C]5[/C][C]0.94[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217109&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217109&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)
12.845630.9915230.96
21.38251270.81119200.71
31.86316140.92135120.84
42.5241570.9715050.94






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.959 (0.041)0.98 (0.02)
(Ps-Ns)/(Ps+Ns)0.959 (0.041)1 (0)0.993 (0.007)
(Pc-Nc)/(Pc+Nc)0.98 (0.02)0.993 (0.007)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) & 0.959 (0.041) & 0.98 (0.02) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.959 (0.041) & 1 (0) & 0.993 (0.007) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.98 (0.02) & 0.993 (0.007) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217109&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]0.959 (0.041)[/C][C]0.98 (0.02)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.959 (0.041)[/C][C]1 (0)[/C][C]0.993 (0.007)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.98 (0.02)[/C][C]0.993 (0.007)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217109&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217109&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)0.959 (0.041)0.98 (0.02)
(Ps-Ns)/(Ps+Ns)0.959 (0.041)1 (0)0.993 (0.007)
(Pc-Nc)/(Pc+Nc)0.98 (0.02)0.993 (0.007)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=217109&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=217109&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217109&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 = pearson ;
Parameters (R input):
par1 = 1 2 3 4 5 ;
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')