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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Mon, 12 Dec 2016 22:30:25 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/12/t1481578243sakd18jdlsw4s4u.htm/, Retrieved Sat, 04 May 2024 03:02:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298998, Retrieved Sat, 04 May 2024 03:02:42 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Survey Scores] [] [2016-12-12 21:30:25] [404ac5ee4f7301873f6a96ef36861981] [Current]

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Histogram

Boxplots

4	2	4	3	5	4
5	3	3	4	5	4
4	4	5	4	5	4
3	4	3	3	4	4
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3	4	5	4	4	5
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3	4	5	3	4	5
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3	4	4	4	4	4
3	4	4	3	5	5
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5	4	4	4	4	4
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5	4	5	4	4	5
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3	4	5	4	4	4
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5	5	2	4	5	4
5	5	5	4	4	4
4	3	5	4	5	5
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3	4	4	3	3	4
3	4	4	4	4	3
4	4	4	3	5	4
4	4	4	4	5	4
5	5	3	4	5	5
2	4	4	4	5	5
4	4	4	4	5	5
3	4	4	4	2	4
4	4	5	4	5	5
4	2	4	4	4	4
4	4	4	3	5	3
4	4	4	3	5	4
5	4	5	3	3	5
3	4	4	3	5	5
3	4	4	3	4	5
4	5	5	5	5	4
4	4	4	4	4	4
4	4	4	5	5	4
3	4	3	4	4	4
4	4	4	4	5	4
3	4	5	3	5	5
3	3	5	4	4	5
4	3	5	4	4	4
4	4	5	4	4	5
3	3	3	4	4	4
4	4	4	4	5	4
4	4	3	4	5	5
4	4	4	4	5	5
5	4	4	4	4	4
5	4	3	5	4	5
4	4	5	4	5	5
3	4	5	4	4	5
4	2	3	3	4	4
4	4	5	4	4	3
4	4	5	4	4	5
4	4	4	4	5	4
4	5	4	4	5	3
3	4	4	3	5	5
4	4	5	4	4	5
5	4	3	4	4	5
5	4	5	5	4	5
4	5	4	4	5	5
5	3	4	4	5	5
4	4	5	4	4	5
5	4	4	4	4	5
5	4	4	5	5	5
4	4	3	3	4	3
4	4	5	4	4	4
4	4	5	4	4	4
3	4	5	4	5	3
4	4	4	4	4	4
4	4	4	3	4	5
3	3	4	3	5	5
4	4	4	3	4	4
3	4	5	4	4	4
4	4	5	4	3	4
5	4	5	1	5	5
5	4	5	4	5	5
4	4	4	4	4	3
4	4	5	3	4	4
3	4	4	3	4	5
4	4	4	4	4	4
4	4	4	4	5	4
4	5	3	4	4	4
3	4	4	4	4	4
4	4	4	3	4	4
4	4	4	4	4	5
3	4	3	3	4	4
4	4	4	3	4	3
3	2	4	2	4	4
4	4	4	3	5	4
5	4	4	3	5	4
2	4	4	3	3	5
3	3	4	4	4	4
5	5	4	4	5	4
4	5	5	4	4	4
5	5	5	5	5	4
4	5	5	4	5	5
4	4	4	3	4	5
3	4	5	4	5	4
4	4	5	4	4	4
4	4	2	4	4	4
4	4	3	4	5	5
4	4	4	4	5	5
5	4	5	3	5	4
4	3	5	4	4	4
4	4	5	4	4	4
3	3	2	3	4	4
4	5	5	4	4	3
4	4	4	3	4	4
4	4	4	4	4	5
3	4	5	3	5	5
4	4	5	4	4	5
5	4	5	4	5	4
4	4	5	4	3	4
2	3	5	4	4	4
4	4	4	4	4	5
4	3	4	3	5	5
4	4	4	4	4	3
4	5	5	5	4	4
5	4	3	4	4	4
5	4	4	3	4	4
3	3	1	4	5	5
4	4	4	4	4	5
4	4	4	4	5	4
2	3	4	5	5	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big 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=298998&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=298998&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298998&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.87	144	6	0.92	117	6	0.9
2	0.96	156	4	0.95	134	4	0.94
3	1.24	204	7	0.93	138	6	0.92
4	0.75	122	3	0.95	114	2	0.97
5	1.33	213	2	0.98	150	2	0.97
6	1.35	214	0	1	149	0	1

\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 & 0.87 & 144 & 6 & 0.92 & 117 & 6 & 0.9 \tabularnewline
2 & 0.96 & 156 & 4 & 0.95 & 134 & 4 & 0.94 \tabularnewline
3 & 1.24 & 204 & 7 & 0.93 & 138 & 6 & 0.92 \tabularnewline
4 & 0.75 & 122 & 3 & 0.95 & 114 & 2 & 0.97 \tabularnewline
5 & 1.33 & 213 & 2 & 0.98 & 150 & 2 & 0.97 \tabularnewline
6 & 1.35 & 214 & 0 & 1 & 149 & 0 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298998&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]0.87[/C][C]144[/C][C]6[/C][C]0.92[/C][C]117[/C][C]6[/C][C]0.9[/C][/ROW]
[ROW][C]2[/C][C]0.96[/C][C]156[/C][C]4[/C][C]0.95[/C][C]134[/C][C]4[/C][C]0.94[/C][/ROW]
[ROW][C]3[/C][C]1.24[/C][C]204[/C][C]7[/C][C]0.93[/C][C]138[/C][C]6[/C][C]0.92[/C][/ROW]
[ROW][C]4[/C][C]0.75[/C][C]122[/C][C]3[/C][C]0.95[/C][C]114[/C][C]2[/C][C]0.97[/C][/ROW]
[ROW][C]5[/C][C]1.33[/C][C]213[/C][C]2[/C][C]0.98[/C][C]150[/C][C]2[/C][C]0.97[/C][/ROW]
[ROW][C]6[/C][C]1.35[/C][C]214[/C][C]0[/C][C]1[/C][C]149[/C][C]0[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298998&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298998&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)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.87	144	6	0.92	117	6	0.9
2	0.96	156	4	0.95	134	4	0.94
3	1.24	204	7	0.93	138	6	0.92
4	0.75	122	3	0.95	114	2	0.97
5	1.33	213	2	0.98	150	2	0.97
6	1.35	214	0	1	149	0	1

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.621 (0.188)	0.398 (0.435)
(Ps-Ns)/(Ps+Ns)	0.621 (0.188)	1 (0)	0.935 (0.006)
(Pc-Nc)/(Pc+Nc)	0.398 (0.435)	0.935 (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) & 0.621 (0.188) & 0.398 (0.435) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.621 (0.188) & 1 (0) & 0.935 (0.006) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.398 (0.435) & 0.935 (0.006) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298998&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]0.621 (0.188)[/C][C]0.398 (0.435)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.621 (0.188)[/C][C]1 (0)[/C][C]0.935 (0.006)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.398 (0.435)[/C][C]0.935 (0.006)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298998&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298998&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)
mean	1 (0)	0.621 (0.188)	0.398 (0.435)
(Ps-Ns)/(Ps+Ns)	0.621 (0.188)	1 (0)	0.935 (0.006)
(Pc-Nc)/(Pc+Nc)	0.398 (0.435)	0.935 (0.006)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0.003)	0.552 (0.126)	0.414 (0.251)
(Ps-Ns)/(Ps+Ns)	0.552 (0.126)	1 (0.006)	0.929 (0.011)
(Pc-Nc)/(Pc+Nc)	0.414 (0.251)	0.929 (0.011)	1 (0.006)

\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) & 0.552 (0.126) & 0.414 (0.251) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.552 (0.126) & 1 (0.006) & 0.929 (0.011) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.414 (0.251) & 0.929 (0.011) & 1 (0.006) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298998&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]0.552 (0.126)[/C][C]0.414 (0.251)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.552 (0.126)[/C][C]1 (0.006)[/C][C]0.929 (0.011)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.414 (0.251)[/C][C]0.929 (0.011)[/C][C]1 (0.006)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298998&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298998&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)
mean	1 (0.003)	0.552 (0.126)	0.414 (0.251)
(Ps-Ns)/(Ps+Ns)	0.552 (0.126)	1 (0.006)	0.929 (0.011)
(Pc-Nc)/(Pc+Nc)	0.414 (0.251)	0.929 (0.011)	1 (0.006)

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code