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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 computationThu, 21 Dec 2017 21:32:47 +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/21/t15138884252xscpi2fp1vw3se.htm/, Retrieved Tue, 14 May 2024 09:59:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310719, Retrieved Tue, 14 May 2024 09:59:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact46

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 
36 10 10 10 10 21
32 8 8 9 15 22
33 8 6 12 14 17
39 9 10 14 14 21
34 5 8 6 8 19
39 10 10 13 19 23
36 8 7 12 17 21
33 9 10 13 18 22
30 8 6 6 10 11
39 7 7 12 15 20
37 10 9 10 16 18
37 10 6 9 12 16
35 9 7 12 13 18
32 4 6 7 10 13
36 4 4 10 14 17
36 8 6 11 15 20
41 9 8 15 20 20
36 10 9 10 9 15
37 8 8 12 12 18
29 5 6 10 13 15
39 10 6 12 16 19
37 8 10 11 12 19
32 7 8 11 14 19
36 8 8 12 15 20
43 8 7 15 19 20
30 9 4 12 16 16
33 8 9 11 16 18
28 6 8 9 14 17
30 8 10 11 14 18
28 8 8 11 14 13
39 5 6 9 13 20
34 9 7 15 18 21
34 8 8 12 15 17
29 8 5 9 15 19
32 8 10 12 15 20
33 6 2 12 13 15
27 6 6 9 14 15
35 9 7 9 15 19
38 8 5 11 14 18
40 9 8 12 19 22
34 10 7 12 16 20
34 8 7 12 16 18
26 8 10 12 12 14
39 7 7 6 10 15
34 7 6 11 11 17
39 10 10 12 13 16
26 8 6 9 14 17
30 7 5 11 11 15
34 10 8 9 11 17
34 7 8 10 16 18
29 7 5 10 9 16
41 9 8 9 16 18
43 9 10 12 19 22
31 8 7 11 13 16
33 6 7 9 15 16
34 8 7 9 14 20
30 9 7 12 15 18
23 2 2 6 11 16
29 6 4 10 14 16
35 8 6 12 15 20
40 8 7 11 17 21
27 7 9 14 16 18
30 8 9 8 13 15
27 6 4 9 15 18
29 10 9 10 14 18
33 10 9 10 15 20
32 10 8 10 14 18
33 8 7 11 12 16
36 8 9 10 12 19
34 7 7 12 15 20
45 10 6 14 17 22
30 5 7 10 13 18
22 3 2 8 5 8
24 2 3 8 7 13
25 3 4 7 10 13
26 4 5 11 15 18
27 2 2 6 9 12
27 6 6 9 9 16
35 8 8 12 15 21
36 8 5 12 14 20
32 5 4 12 11 18
35 10 10 9 18 22
35 9 10 15 20 23
36 8 10 15 20 23
37 9 9 13 16 21
33 8 5 9 15 16
25 5 5 12 14 14
35 7 7 9 13 18
37 9 10 15 18 22
36 8 9 11 14 20
35 4 8 11 12 18
29 7 8 6 9 12
35 8 8 14 19 17
31 7 8 11 13 15
30 7 8 8 12 18
37 9 7 10 14 18
36 6 6 10 6 15
35 7 8 9 14 16
32 4 2 8 11 15
34 6 5 9 11 16
37 10 4 10 14 19
36 9 9 11 12 19
39 10 10 14 19 23
37 8 6 12 13 20
31 4 4 9 14 18
40 8 10 13 17 21
38 5 6 8 12 19
35 8 7 12 16 18
38 9 7 14 15 19
32 8 8 9 15 17
41 4 6 10 15 21
28 8 5 12 16 19
40 10 6 12 15 24
25 6 7 9 12 12
28 7 6 9 13 15
37 10 9 12 14 18
37 9 9 15 17 19
40 8 7 12 14 22
26 3 6 11 14 19
30 8 7 8 14 16
32 7 7 11 15 19
31 7 8 11 11 18
28 8 7 10 11 18
34 8 8 12 16 19
39 7 7 9 12 21
33 7 4 11 12 19
43 9 10 15 19 22
37 9 8 14 18 23
31 9 8 6 16 17
31 4 2 9 16 18
34 6 6 9 13 19
32 6 4 8 11 15
27 6 4 7 10 14
34 8 9 10 14 18
28 3 2 6 14 17
32 8 6 9 14 19
39 8 7 9 16 16
28 6 4 7 10 14
39 10 10 11 16 20
32 2 3 9 7 16
36 9 7 12 16 18
31 6 4 9 15 16
39 6 8 10 17 21
23 5 4 11 11 16
25 4 5 7 11 14
32 7 6 12 10 16
32 5 5 8 13 19
36 8 9 13 14 19
39 6 6 11 13 19
31 9 8 11 13 18
32 6 4 12 12 16
28 4 4 11 10 14
34 7 8 12 15 19
28 2 4 3 6 11
38 8 10 10 15 18
35 9 8 13 15 18
32 6 5 10 11 16
26 5 3 6 14 20
32 7 7 11 14 18
28 8 6 12 16 20
31 4 5 9 12 16
33 9 5 10 15 18
38 9 9 15 20 19
38 9 2 9 12 19
36 7 7 6 9 15
31 5 7 9 13 17
36 7 5 15 15 21
43 9 9 15 19 24
37 8 4 9 11 16
28 6 5 11 11 13
35 9 9 9 17 21
34 8 7 11 15 16
40 7 6 10 14 17
31 7 8 9 15 17
41 7 7 6 11 18
35 8 6 12 12 18
38 10 8 13 15 23
37 6 6 12 16 20
31 6 7 12 16 20

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310719&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310719&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 time1 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)
130.5454670117901
24.2877150.9917050.94
33.7568080.9816880.91
47.5113440117801
510.8219370117901
614.9426750117901

\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 & 30.54 & 5467 & 0 & 1 & 179 & 0 & 1 \tabularnewline
2 & 4.28 & 771 & 5 & 0.99 & 170 & 5 & 0.94 \tabularnewline
3 & 3.75 & 680 & 8 & 0.98 & 168 & 8 & 0.91 \tabularnewline
4 & 7.51 & 1344 & 0 & 1 & 178 & 0 & 1 \tabularnewline
5 & 10.82 & 1937 & 0 & 1 & 179 & 0 & 1 \tabularnewline
6 & 14.94 & 2675 & 0 & 1 & 179 & 0 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310719&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]30.54[/C][C]5467[/C][C]0[/C][C]1[/C][C]179[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]2[/C][C]4.28[/C][C]771[/C][C]5[/C][C]0.99[/C][C]170[/C][C]5[/C][C]0.94[/C][/ROW]
[ROW][C]3[/C][C]3.75[/C][C]680[/C][C]8[/C][C]0.98[/C][C]168[/C][C]8[/C][C]0.91[/C][/ROW]
[ROW][C]4[/C][C]7.51[/C][C]1344[/C][C]0[/C][C]1[/C][C]178[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]5[/C][C]10.82[/C][C]1937[/C][C]0[/C][C]1[/C][C]179[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]6[/C][C]14.94[/C][C]2675[/C][C]0[/C][C]1[/C][C]179[/C][C]0[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310719&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)
130.5454670117901
24.2877150.9917050.94
33.7568080.9816880.91
47.5113440117801
510.8219370117901
614.9426750117901






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.576 (0.231)0.602 (0.206)
(Ps-Ns)/(Ps+Ns)0.576 (0.231)1 (0)0.989 (0)
(Pc-Nc)/(Pc+Nc)0.602 (0.206)0.989 (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) & 0.576 (0.231) & 0.602 (0.206) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.576 (0.231) & 1 (0) & 0.989 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.602 (0.206) & 0.989 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310719&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]0.576 (0.231)[/C][C]0.602 (0.206)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.576 (0.231)[/C][C]1 (0)[/C][C]0.989 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.602 (0.206)[/C][C]0.989 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310719&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)0.576 (0.231)0.602 (0.206)
(Ps-Ns)/(Ps+Ns)0.576 (0.231)1 (0)0.989 (0)
(Pc-Nc)/(Pc+Nc)0.602 (0.206)0.989 (0)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.003)0.775 (0.042)0.775 (0.042)
(Ps-Ns)/(Ps+Ns)0.775 (0.042)1 (0.016)1 (0.016)
(Pc-Nc)/(Pc+Nc)0.775 (0.042)1 (0.016)1 (0.016)

\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 (0.003) & 0.775 (0.042) & 0.775 (0.042) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.775 (0.042) & 1 (0.016) & 1 (0.016) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.775 (0.042) & 1 (0.016) & 1 (0.016) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310719&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 (0.003)[/C][C]0.775 (0.042)[/C][C]0.775 (0.042)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.775 (0.042)[/C][C]1 (0.016)[/C][C]1 (0.016)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.775 (0.042)[/C][C]1 (0.016)[/C][C]1 (0.016)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310719&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310719&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 (0.003)0.775 (0.042)0.775 (0.042)
(Ps-Ns)/(Ps+Ns)0.775 (0.042)1 (0.016)1 (0.016)
(Pc-Nc)/(Pc+Nc)0.775 (0.042)1 (0.016)1 (0.016)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par4 = 12 ;
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')