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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationWed, 03 Dec 2014 13:36:03 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/03/t141761377098rw1db8go7exx6.htm/, Retrieved Thu, 31 Oct 2024 23:05:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=262950, Retrieved Thu, 31 Oct 2024 23:05:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
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] [WS3 question 1] [2014-10-15 15:38:25] [a6b2572b29932aa41ecec373f1b28823]
-    D      [Survey Scores] [] [2014-11-30 11:51:47] [80a885d02035c87be624c190e38c794d]
-    D        [Survey Scores] [] [2014-12-02 09:24:03] [80a885d02035c87be624c190e38c794d]
-    D          [Survey Scores] [] [2014-12-02 09:30:58] [80a885d02035c87be624c190e38c794d]
-    D            [Survey Scores] [] [2014-12-03 13:03:09] [80a885d02035c87be624c190e38c794d]
-    D              [Survey Scores] [] [2014-12-03 13:24:06] [80a885d02035c87be624c190e38c794d]
-    D                [Survey Scores] [] [2014-12-03 13:28:13] [80a885d02035c87be624c190e38c794d]
-    D                  [Survey Scores] [] [2014-12-03 13:32:05] [80a885d02035c87be624c190e38c794d]
-    D                      [Survey Scores] [] [2014-12-03 13:36:03] [4b67a948f2e7df32913e04ba402e80f8] [Current]
-    D                        [Survey Scores] [] [2014-12-03 13:42:47] [80a885d02035c87be624c190e38c794d]
-    D                          [Survey Scores] [] [2014-12-03 13:47:00] [80a885d02035c87be624c190e38c794d]
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Dataseries X:
6	5	6	6
4	4	4	4
7	5	7	7
6	6	6	7
7	5	6	5
7	4	6	7
7	6	6	7
5	4	5	6
6	6	6	6
1	6	6	1
7	7	7	7
7	5	6	7
6	4	5	6
6	5	3	5
7	3	5	7
6	5	5	6
6	3	6	6
4	4	4	5
6	4	5	6
6	5	6	6
5	4	4	3
6	2	2	5
7	6	5	6
6	6	6	7
6	6	5	6
5	4	5	5
6	6	6	6
4	2	4	4
6	3	5	6
6	5	5	7
7	1	2	2
7	2	6	7
5	3	5	5
6	4	5	6
6	5	6	6
6	5	6	5
7	7	7	7
6	4	4	6
6	5	5	6
7	4	6	7
4	5	5	5
4	1	2	2
6	5	5	7
6	6	5	6
6	6	4	6
5	5	5	5
6	5	5	7
6	6	6	6
5	2	5	5
5	4	5	5
6	1	4	6
6	4	6	7
5	5	4	5
7	6	5	6
5	2	5	3
6	7	4	5
7	5	6	7
7	6	7	7
7	5	5	6
5	3	4	4
6	5	6	7
7	2	6	7
7	7	6	7
7	7	7	7
6	5	5	7
7	6	6	6
6	5	5	5
6	5	5	6
7	5	6	7
6	6	6	7
4	5	5	5
6	5	6	7
6	4	5	6
5	6	4	3
5	3	4	5
6	4	3	4
7	6	6	7
4	1	1	2
6	5	7	7
7	4	5	6
6	4	4	6
7	5	4	6
5	2	4	6
7	5	5	7
4	5	5	6
4	6	4	5
6	7	6	7
7	2	2	2
5	5	5	5
7	7	6	6
5	4	6	6
6	6	6	6
6	5	6	6
4	5	2	5
7	5	6	6
5	4	4	5
7	4	4	6
6	4	4	3
5	5	4	5
5	6	5	6
7	4	6	6
6	7	7	7
6	5	5	6
7	3	6	6
7	6	5	7
7	6	6	7
6	5	4	7
7	5	6	7
7	4	5	7
1	4	1	2
6	6	6	6
5	2	2	5
5	3	4	5
6	4	4	7
6	3	6	6
6	6	7	6
6	2	5	5
5	5	4	6
7	5	6	7
5	4	6	5
7	6	6	5
6	4	5	7
5	3	5	3
5	5	5	5
5	6	5	5
6	5	5	6
3	2	5	5
6	4	5	6
7	5	6	7
4	4	4	4
7	7	7	7
6	4	6	6
5	5	4	5
6	3	4	4
6	5	6	6
7	7	7	7
5	5	4	5
6	6	6	6
5	3	3	5
5	5	3	6
5	7	3	4
1	4	2	5
6	1	4	5
5	4	2	4
5	5	2	5
7	6	4	6
4	7	5	5
5	4	5	6
6	5	3	5
5	5	4	6
5	5	5	5
6	5	6	6
6	4	6	6
7	3	5	5
6	6	6	6
5	5	5	6
6	5	5	7
6	5	4	7
6	5	4	6
7	5	7	7
4	4	4	4
7	7	7	7
7	5	6	6
7	7	7	7
6	1	2	5
5	2	4	5
7	4	4	7
5	5	3	5
7	6	4	6
6	5	1	6
6	4	6	6
2	5	2	4
5	5	5	5
7	5	5	7
7	3	7	7
6	7	6	6
7	5	5	6
7	5	5	7
6	5	5	6
5	6	6	7
6	5	6	7
6	4	7	7
6	6	7	6
7	6	7	7
6	7	7	7
3	4	4	3
6	4	6	5
6	3	3	5
6	5	6	6
7	6	5	7
5	5	5	5
5	6	5	5
5	6	6	7
6	7	7	7
3	3	3	3
6	6	7	7
7	5	4	6
6	6	5	7
6	6	6	6
5	5	5	5
4	4	7	7
7	5	5	6
5	5	6	6
6	5	5	5
3	3	2	5
7	1	6	7
5	6	6	3
6	2	5	5
6	3	5	5
6	6	7	6
6	6	6	6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262950&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]0 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=262950&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262950&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







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)
11.77389150.9318980.92
20.68208650.52132380.55
31254420.72148240.72
41.72384210.9187140.86

\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 & 1.77 & 389 & 15 & 0.93 & 189 & 8 & 0.92 \tabularnewline
2 & 0.68 & 208 & 65 & 0.52 & 132 & 38 & 0.55 \tabularnewline
3 & 1 & 254 & 42 & 0.72 & 148 & 24 & 0.72 \tabularnewline
4 & 1.72 & 384 & 21 & 0.9 & 187 & 14 & 0.86 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262950&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]1.77[/C][C]389[/C][C]15[/C][C]0.93[/C][C]189[/C][C]8[/C][C]0.92[/C][/ROW]
[ROW][C]2[/C][C]0.68[/C][C]208[/C][C]65[/C][C]0.52[/C][C]132[/C][C]38[/C][C]0.55[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]254[/C][C]42[/C][C]0.72[/C][C]148[/C][C]24[/C][C]0.72[/C][/ROW]
[ROW][C]4[/C][C]1.72[/C][C]384[/C][C]21[/C][C]0.9[/C][C]187[/C][C]14[/C][C]0.86[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262950&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262950&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)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.77389150.9318980.92
20.68208650.52132380.55
31254420.72148240.72
41.72384210.9187140.86







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.979 (0.021)0.975 (0.025)
(Ps-Ns)/(Ps+Ns)0.979 (0.021)1 (0)0.996 (0.004)
(Pc-Nc)/(Pc+Nc)0.975 (0.025)0.996 (0.004)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) & 0.979 (0.021) & 0.975 (0.025) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.979 (0.021) & 1 (0) & 0.996 (0.004) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.975 (0.025) & 0.996 (0.004) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262950&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]0.979 (0.021)[/C][C]0.975 (0.025)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.979 (0.021)[/C][C]1 (0)[/C][C]0.996 (0.004)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.975 (0.025)[/C][C]0.996 (0.004)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262950&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262950&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)
mean1 (0)0.979 (0.021)0.975 (0.025)
(Ps-Ns)/(Ps+Ns)0.979 (0.021)1 (0)0.996 (0.004)
(Pc-Nc)/(Pc+Nc)0.975 (0.025)0.996 (0.004)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (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=262950&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=262950&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262950&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)
mean1 (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):
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')