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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

Tue, 16 Dec 2014 16:08:47 +0000

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/2014/Dec/16/t1418746828j5agkp0l32xlb7b.htm/, Retrieved Thu, 31 Oct 2024 22:47:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269808, Retrieved Thu, 31 Oct 2024 22:47:26 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

108

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]
- RMP   [Survey Scores] [] [2014-10-09 22:08:50] [32b17a345b130fdf5cc88718ed94a974]
-    D    [Survey Scores] [pearson/kendall c...] [2014-10-16 21:11:53] [0f2441473984dd788bd8148394ed78a8]
- R  D        [Survey Scores] [] [2014-12-16 16:08:47] [6870495cd5e22452491bd29e9b20b7c8] [Current]

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Dataseries X:

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Histogram

Boxplots

4	2	2	3
4	5	3	3
4	5	5	5
3	3	5	5
6	6	6	6
4	4	4	3
4	4	4	5
5	5	5	4
5	3	6	5
7	7	7	7
7	6	7	6
3	4	3	5
7	7	6	6
2	3	5	6
5	5	7	7
6	5	7	7
4	3	4	4
6	5	5	5
7	6	7	7
7	5	7	7
7	7	6	6
6	6	5	5
5	4	6	6
5	6	5	6
4	5	6	5
6	5	5	6
6	5	4	6
2	2	2	2
6	5	6	5
4	4	5	5
3	5	7	5
6	6	6	6
4	5	4	4
3	5	5	7
7	6	5	5
5	5	6	6
4	4	5	6
4	4	4	3
6	3	5	6
5	5	6	6
5	2	4	6
7	5	6	6
4	5	4	4
6	6	6	7
4	4	5	5
6	6	6	6
5	6	6	6
4	5	5	6
6	5	6	5
4	5	6	7
3	3	4	5
5	4	4	4
5	5	4	5
4	6	6	6
5	4	6	6
5	4	5	7
5	5	5	5
5	6	5	5
3	2	5	5
5	1	6	6
6	5	5	6
2	3	6	5
6	7	6	5
4	5	5	5
4	5	5	6
1	1	2	2
5	3	4	3
4	4	5	5
6	5	5	5
6	5	6	6
5	5	5	5
5	5	5	5
4	4	5	5
6	6	7	6
4	4	4	4
5	5	5	5
4	4	3	3
4	4	7	7
4	4	7	5
6	2	4	5
5	6	5	6
6	4	6	6
5	5	5	5
4	4	5	4
6	5	5	6
3	4	5	5
5	5	6	6
5	5	5	6
6	7	6	6
5	5	4	5
6	6	6	6
5	4	4	4
6	4	6	6
6	5	5	6
5	4	4	4
5	7	7	7
4	5	5	5
4	5	5	6
5	4	5	5
6	4	6	5
6	5	6	7
5	5	6	5
4	5	5	5
3	4	2	4
7	6	7	7
6	5	6	5
5	5	5	6
6	5	5	6
5	6	5	6
5	6	5	5
5	4	5	5
4	1	2	4
6	5	4	4
6	4	5	6
5	5	5	4
2	2	2	2
6	6	5	6
4	4	4	5
5	6	7	7
6	6	6	6
5	6	5	6
5	6	6	6
3	5	4	5
7	5	6	6
6	5	5	6
5	5	5	6
6	1	6	6
5	5	4	5
4	4	4	4
5	4	7	7
5	6	6	6
4	5	6	5
7	6	5	6
6	7	6	6
5	5	5	5
5	6	6	6
5	6	5	5
7	7	4	5
3	3	2	3
7	7	6	7
5	6	6	5
4	3	3	6
3	5	5	5
7	4	5	7
6	5	7	6
5	5	4	6
5	5	6	4
3	3	4	4
3	7	7	6
4	4	3	5
5	4	7	5
5	5	4	5
7	6	7	7
2	2	2	7
5	3	5	4
6	5	2	5
5	5	5	5
5	5	6	6
4	4	5	5
3	1	1	1
6	5	6	5
3	4	5	3
4	4	4	5
2	3	2	3
5	5	4	7
5	5	6	7
5	4	4	5
5	5	5	5
6	7	7	7
5	1	1	6
5	5	5	5
5	4	5	6
6	6	5	5
4	5	6	5
6	5	6	7
6	5	6	6
5	2	6	6
4	5	6	7
7	6	6	5
5	5	6	5
5	4	5	5
5	4	5	6
2	2	6	6
4	1	6	6
6	6	6	7
5	3	3	5
6	5	6	6
6	4	5	5
6	6	6	5
6	5	5	6
3	4	5	3
4	4	4	4
5	5	6	7
6	6	7	6
2	3	5	4
5	4	4	5
5	4	3	3
7	6	7	7
5	5	7	5
7	7	6	6
7	6	7	5
5	5	5	4
2	6	5	6
6	5	7	6
5	5	4	5
6	6	7	6
5	5	5	5
5	4	4	4
3	4	2	4
5	5	5	5
5	5	4	6
6	4	7	7
7	5	6	7
5	5	5	5
5	4	5	6
5	5	5	5
2	2	3	4
4	5	7	7
5	4	5	5
7	7	6	6
6	6	7	7
5	5	5	5
5	6	6	6
5	5	4	5
5	6	6	6
6	7	7	7
4	4	3	5
6	7	6	7
6	6	7	7
5	5	5	5
4	4	2	2
5	5	5	5
5	5	5	3
7	7	7	7
6	5	6	7
6	6	6	6
6	6	6	6
3	3	3	3
6	6	5	6
3	3	4	6
3	5	5	5
7	6	6	6
5	3	4	6
1	1	1	4
7	5	3	4
3	3	6	5
5	5	5	5
3	5	6	5
3	3	2	2
7	6	6	6
6	5	6	6
5	6	5	7
6	6	5	6
6	4	5	5
5	6	6	7
5	3	4	5
5	5	6	5
7	2	7	6
3	3	4	4
4	3	6	6
2	5	7	7
7	5	6	6
3	3	3	2
5	5	5	6
5	5	6	6
5	6	5	6
5	4	4	6
3	2	5	5
4	5	5	6
6	5	5	6
5	5	5	5
3	5	5	5
4	4	5	7
NA	NA	NA	NA
NA	NA	NA	NA
5	5	5	6
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA

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	'Sir Maurice George Kendall' @ kendall.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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269808&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269808&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269808&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	'Sir Maurice George Kendall' @ kendall.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	0.91	305	55	0.69	188	40	0.65
2	0.68	257	72	0.56	174	44	0.6
3	1.1	349	47	0.76	206	28	0.76
4	1.37	403	28	0.87	228	20	0.84

\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 & 0.91 & 305 & 55 & 0.69 & 188 & 40 & 0.65 \tabularnewline
2 & 0.68 & 257 & 72 & 0.56 & 174 & 44 & 0.6 \tabularnewline
3 & 1.1 & 349 & 47 & 0.76 & 206 & 28 & 0.76 \tabularnewline
4 & 1.37 & 403 & 28 & 0.87 & 228 & 20 & 0.84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269808&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]0.91[/C][C]305[/C][C]55[/C][C]0.69[/C][C]188[/C][C]40[/C][C]0.65[/C][/ROW]
[ROW][C]2[/C][C]0.68[/C][C]257[/C][C]72[/C][C]0.56[/C][C]174[/C][C]44[/C][C]0.6[/C][/ROW]
[ROW][C]3[/C][C]1.1[/C][C]349[/C][C]47[/C][C]0.76[/C][C]206[/C][C]28[/C][C]0.76[/C][/ROW]
[ROW][C]4[/C][C]1.37[/C][C]403[/C][C]28[/C][C]0.87[/C][C]228[/C][C]20[/C][C]0.84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269808&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269808&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	0.91	305	55	0.69	188	40	0.65
2	0.68	257	72	0.56	174	44	0.6
3	1.1	349	47	0.76	206	28	0.76
4	1.37	403	28	0.87	228	20	0.84

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.995 (0.005)	0.986 (0.014)
(Ps-Ns)/(Ps+Ns)	0.995 (0.005)	1 (0)	0.971 (0.029)
(Pc-Nc)/(Pc+Nc)	0.986 (0.014)	0.971 (0.029)	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) & 0.995 (0.005) & 0.986 (0.014) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.995 (0.005) & 1 (0) & 0.971 (0.029) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.986 (0.014) & 0.971 (0.029) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269808&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]0.995 (0.005)[/C][C]0.986 (0.014)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.995 (0.005)[/C][C]1 (0)[/C][C]0.971 (0.029)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.986 (0.014)[/C][C]0.971 (0.029)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269808&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269808&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)	0.995 (0.005)	0.986 (0.014)
(Ps-Ns)/(Ps+Ns)	0.995 (0.005)	1 (0)	0.971 (0.029)
(Pc-Nc)/(Pc+Nc)	0.986 (0.014)	0.971 (0.029)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (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=269808&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=269808&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269808&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 (0.083)	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)

Parameters (Session):

par1 = 1 2 3 4 5 6 7 ;

Parameters (R input):

par1 = 1 2 3 4 5 6 7 ;

R code (references can be found in the software module):

par1 <- ''
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