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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, 12 Dec 2017 16:07:05 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/12/t1513093119vz4xc7jy9gg82h9.htm/, Retrieved Thu, 31 Oct 2024 23:04:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309140, Retrieved Thu, 31 Oct 2024 23:04:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309140&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309140&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309140&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center






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)
10.49112250.6494210.63
20.3997280.5589250.56
30.52108150.7691140.73
40.79157150.83127120.83
50.7313770.911170.88

\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 & 0.49 & 112 & 25 & 0.64 & 94 & 21 & 0.63 \tabularnewline
2 & 0.39 & 97 & 28 & 0.55 & 89 & 25 & 0.56 \tabularnewline
3 & 0.52 & 108 & 15 & 0.76 & 91 & 14 & 0.73 \tabularnewline
4 & 0.79 & 157 & 15 & 0.83 & 127 & 12 & 0.83 \tabularnewline
5 & 0.73 & 137 & 7 & 0.9 & 111 & 7 & 0.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309140&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]0.49[/C][C]112[/C][C]25[/C][C]0.64[/C][C]94[/C][C]21[/C][C]0.63[/C][/ROW]
[ROW][C]2[/C][C]0.39[/C][C]97[/C][C]28[/C][C]0.55[/C][C]89[/C][C]25[/C][C]0.56[/C][/ROW]
[ROW][C]3[/C][C]0.52[/C][C]108[/C][C]15[/C][C]0.76[/C][C]91[/C][C]14[/C][C]0.73[/C][/ROW]
[ROW][C]4[/C][C]0.79[/C][C]157[/C][C]15[/C][C]0.83[/C][C]127[/C][C]12[/C][C]0.83[/C][/ROW]
[ROW][C]5[/C][C]0.73[/C][C]137[/C][C]7[/C][C]0.9[/C][C]111[/C][C]7[/C][C]0.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309140&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309140&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)
10.49112250.6494210.63
20.3997280.5589250.56
30.52108150.7691140.73
40.79157150.83127120.83
50.7313770.911170.88






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.908 (0.033)0.94 (0.017)
(Ps-Ns)/(Ps+Ns)0.908 (0.033)1 (0)0.995 (0)
(Pc-Nc)/(Pc+Nc)0.94 (0.017)0.995 (0)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) & 0.908 (0.033) & 0.94 (0.017) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.908 (0.033) & 1 (0) & 0.995 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.94 (0.017) & 0.995 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309140&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]0.908 (0.033)[/C][C]0.94 (0.017)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.908 (0.033)[/C][C]1 (0)[/C][C]0.995 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.94 (0.017)[/C][C]0.995 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309140&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309140&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)0.908 (0.033)0.94 (0.017)
(Ps-Ns)/(Ps+Ns)0.908 (0.033)1 (0)0.995 (0)
(Pc-Nc)/(Pc+Nc)0.94 (0.017)0.995 (0)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.017)0.8 (0.083)0.8 (0.083)
(Ps-Ns)/(Ps+Ns)0.8 (0.083)1 (0.017)1 (0.017)
(Pc-Nc)/(Pc+Nc)0.8 (0.083)1 (0.017)1 (0.017)

\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 (0.017) & 0.8 (0.083) & 0.8 (0.083) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.8 (0.083) & 1 (0.017) & 1 (0.017) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.8 (0.083) & 1 (0.017) & 1 (0.017) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309140&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 (0.017)[/C][C]0.8 (0.083)[/C][C]0.8 (0.083)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.8 (0.083)[/C][C]1 (0.017)[/C][C]1 (0.017)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.8 (0.083)[/C][C]1 (0.017)[/C][C]1 (0.017)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309140&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309140&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 (0.017)0.8 (0.083)0.8 (0.083)
(Ps-Ns)/(Ps+Ns)0.8 (0.083)1 (0.017)1 (0.017)
(Pc-Nc)/(Pc+Nc)0.8 (0.083)1 (0.017)1 (0.017)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 ;
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)
}
print(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')