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Author

*The author of this computation has been verified*

R Software Module

Title produced by software

Survey Scores

Date of computation

Wed, 10 Dec 2014 13:26:10 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t14182179859815a7z80al1vg3.htm/, Retrieved Tue, 10 Feb 2026 09:20:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265136, Retrieved Tue, 10 Feb 2026 09:20:11 +0000

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Estimated Impact

360

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

-     [Survey Scores] [Kendall Tau NUMGRAF] [2014-12-10 13:15:38] [bcf5edf18529a33bd1494456d2c6cb9a]
-    D  [Survey Scores] [Kendall Tau NUMGRAF] [2014-12-10 13:21:05] [bcf5edf18529a33bd1494456d2c6cb9a]
- RM        [Survey Scores] [Kendall Tau NUMGRAF] [2014-12-10 13:26:10] [ddb851b9ced255c1d64c58a7ca49fb28] [Current]

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0 1 1 1 1 0
1 1 1 1 1 0
1 1 1 1 1 1
1 1 1 1 0 1
1 0 1 1 1 0
0 0 0 0 0 0
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1 1 1 1 1 1
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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265136&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265136&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	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

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	0.05	195	157.5	0.11	390	315	0.11
2	0.38	310.5	42	0.76	621	84	0.76
3	0.38	308.5	44	0.75	617	88	0.75
4	0.3	283.5	69	0.61	567	138	0.61
5	0.34	296	56.5	0.68	592	113	0.68
6	0.22	253.5	99	0.44	507	198	0.44

\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 & 0.05 & 195 & 157.5 & 0.11 & 390 & 315 & 0.11 \tabularnewline
2 & 0.38 & 310.5 & 42 & 0.76 & 621 & 84 & 0.76 \tabularnewline
3 & 0.38 & 308.5 & 44 & 0.75 & 617 & 88 & 0.75 \tabularnewline
4 & 0.3 & 283.5 & 69 & 0.61 & 567 & 138 & 0.61 \tabularnewline
5 & 0.34 & 296 & 56.5 & 0.68 & 592 & 113 & 0.68 \tabularnewline
6 & 0.22 & 253.5 & 99 & 0.44 & 507 & 198 & 0.44 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265136&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]0.05[/C][C]195[/C][C]157.5[/C][C]0.11[/C][C]390[/C][C]315[/C][C]0.11[/C][/ROW]
[ROW][C]2[/C][C]0.38[/C][C]310.5[/C][C]42[/C][C]0.76[/C][C]621[/C][C]84[/C][C]0.76[/C][/ROW]
[ROW][C]3[/C][C]0.38[/C][C]308.5[/C][C]44[/C][C]0.75[/C][C]617[/C][C]88[/C][C]0.75[/C][/ROW]
[ROW][C]4[/C][C]0.3[/C][C]283.5[/C][C]69[/C][C]0.61[/C][C]567[/C][C]138[/C][C]0.61[/C][/ROW]
[ROW][C]5[/C][C]0.34[/C][C]296[/C][C]56.5[/C][C]0.68[/C][C]592[/C][C]113[/C][C]0.68[/C][/ROW]
[ROW][C]6[/C][C]0.22[/C][C]253.5[/C][C]99[/C][C]0.44[/C][C]507[/C][C]198[/C][C]0.44[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265136&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	0.05	195	157.5	0.11	390	315	0.11
2	0.38	310.5	42	0.76	621	84	0.76
3	0.38	308.5	44	0.75	617	88	0.75
4	0.3	283.5	69	0.61	567	138	0.61
5	0.34	296	56.5	0.68	592	113	0.68
6	0.22	253.5	99	0.44	507	198	0.44

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	1 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	1 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	1 (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) & 1 (0) & 1 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265136&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]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265136&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265136&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)	1 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	1 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	1 (0)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0.006)	0.966 (0.007)	0.966 (0.007)
(Ps-Ns)/(Ps+Ns)	0.966 (0.007)	1 (0.003)	1 (0.003)
(Pc-Nc)/(Pc+Nc)	0.966 (0.007)	1 (0.003)	1 (0.003)

\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 (0.006) & 0.966 (0.007) & 0.966 (0.007) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.966 (0.007) & 1 (0.003) & 1 (0.003) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.966 (0.007) & 1 (0.003) & 1 (0.003) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265136&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 (0.006)[/C][C]0.966 (0.007)[/C][C]0.966 (0.007)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.966 (0.007)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.966 (0.007)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265136&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265136&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 (0.006)	0.966 (0.007)	0.966 (0.007)
(Ps-Ns)/(Ps+Ns)	0.966 (0.007)	1 (0.003)	1 (0.003)
(Pc-Nc)/(Pc+Nc)	0.966 (0.007)	1 (0.003)	1 (0.003)

Parameters (Session):

par1 = 0 1 ;

Parameters (R input):

par1 = 0 1 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code