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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 computationSat, 13 Nov 2010 14:57:53 +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/2010/Nov/13/t12896601920sy4j7ym31ndu1u.htm/, Retrieved Thu, 02 May 2024 10:41:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=94399, Retrieved Thu, 02 May 2024 10:41:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

Tree of Dependent Computations

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]
-   PD  [Survey Scores] [Question 1 Extrin...] [2010-10-15 10:55:08] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-   PD      [Survey Scores] [IC knowing people] [2010-11-13 14:57:53] [9ea95e194e0eb2a674315798620d5bc6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4	4	3	3
2	2	2	2
2	4	4	2
2	3	1	1
2	3	2	3
2	1	2	2
5	4	3	4
4	3	2	2
4	4	2	4
2	1	2	1
4	4	4	4
2	3	3	3
4	4	4	4
4	4	2	2
1	1	3	2
4	4	3	2
3	2	3	3
4	4	4	3
1	2	2	2
2	3	2	2
1	3	2	1
4	3	3	4
4	3	4	4
1	2	2	2
4	4	3	4
5	4	4	4
4	4	3	4
4	4	3	3
4	4	3	3
2	2	2	2
2	2	2	2
4	4	4	2
4	3	3	4
2	2	3	1
3	2	2	4
4	4	4	4
3	3	3	1
2	2	2	2
4	4	3	3
4	4	4	4
3	3	4	3
1	1	2	1
2	2	1	3
4	2	2	2
2	2	3	1
3	4	3	3
4	3	4	4
1	2	2	1
3	2	3	4
4	4	4	4
1	1	2	1
4	5	2	4
3	2	3	4
1	3	2	2
1	4	4	4
4	4	3	3
4	3	3	2
4	4	4	4
2	2	4	2
4	3	4	4
2	2	2	2
4	4	4	4
5	5	4	5
3	3	4	4
2	1	2	1
4	3	3	3
4	4	3	4
2	2	2	1
3	3	4	3
1	1	1	1
4	3	3	4
4	2	3	4
4	3	2	2
4	4	2	4
3	3	3	3
4	4	3	4
3	4	3	4
3	3	3	4
2	2	3	1
1	1	2	2
2	2	2	1
4	3	3	3
3	4	3	3
5	1	2	3
1	1	2	1
3	3	3	3
2	2	2	2
3	2	3	3
4	3	3	4
3	2	2	2
3	2	3	2
4	3	3	3
4	4	4	4
4	4	4	4
2	2	3	4
2	2	2	2
1	1	1	1
1	2	2	2
4	3	3	4
2	3	3	3
4	4	5	4
3	4	4	4
5	4	5	3
1	0	2	2
1	1	1	1
2	3	3	2
4	2	3	2
4	3	4	4
3	3	2	2
4	2	2	1
4	3	3	2
5	2	4	4
1	2	2	2
4	3	3	3
4	2	3	3
4	3	4	3
2	4	4	4
2	2	2	2
4	4	3	4
3	3	2	4
3	3	3	3
4	4	4	4
2	2	2	3
4	3	4	4
4	4	4	3
1	1	2	2
4	4	3	3
4	4	3	4
3	2	3	2
1	1	3	1
4	4	4	2
3	2	3	4
2	2	2	2
3	3	3	2
4	3	3	3
2	2	3	2
4	3	4	4
4	3	3	3
3	4	4	4
4	3	4	3
4	4	4	4
4	3	3	4
4	4	3	3
3	3	2	2
3	2	3	2
1	1	1	1
2	2	2	2
4	4	4	3
4	4	4	4
3	3	3	3
3	3	3	3
4	3	4	4
3	2	2	2
4	0	4	4
4	4	3	3
4	2	3	2

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94399&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94399&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94399&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






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)
10.0681710.0775510.19
2-0.185179-0.224960-0.1
3-0.14358-0.154152-0.12
4-0.195584-0.215464-0.08

\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 & 0.06 & 81 & 71 & 0.07 & 75 & 51 & 0.19 \tabularnewline
2 & -0.18 & 51 & 79 & -0.22 & 49 & 60 & -0.1 \tabularnewline
3 & -0.1 & 43 & 58 & -0.15 & 41 & 52 & -0.12 \tabularnewline
4 & -0.19 & 55 & 84 & -0.21 & 54 & 64 & -0.08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94399&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]0.06[/C][C]81[/C][C]71[/C][C]0.07[/C][C]75[/C][C]51[/C][C]0.19[/C][/ROW]
[ROW][C]2[/C][C]-0.18[/C][C]51[/C][C]79[/C][C]-0.22[/C][C]49[/C][C]60[/C][C]-0.1[/C][/ROW]
[ROW][C]3[/C][C]-0.1[/C][C]43[/C][C]58[/C][C]-0.15[/C][C]41[/C][C]52[/C][C]-0.12[/C][/ROW]
[ROW][C]4[/C][C]-0.19[/C][C]55[/C][C]84[/C][C]-0.21[/C][C]54[/C][C]64[/C][C]-0.08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94399&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94399&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)
10.0681710.0775510.19
2-0.185179-0.224960-0.1
3-0.14358-0.154152-0.12
4-0.195584-0.215464-0.08






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.99 (0.01)0.896 (0.104)
(Ps-Ns)/(Ps+Ns)0.99 (0.01)1 (0)0.947 (0.053)
(Pc-Nc)/(Pc+Nc)0.896 (0.104)0.947 (0.053)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) & 0.99 (0.01) & 0.896 (0.104) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.99 (0.01) & 1 (0) & 0.947 (0.053) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.896 (0.104) & 0.947 (0.053) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94399&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]0.99 (0.01)[/C][C]0.896 (0.104)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.99 (0.01)[/C][C]1 (0)[/C][C]0.947 (0.053)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.896 (0.104)[/C][C]0.947 (0.053)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94399&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94399&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)0.99 (0.01)0.896 (0.104)
(Ps-Ns)/(Ps+Ns)0.99 (0.01)1 (0)0.947 (0.053)
(Pc-Nc)/(Pc+Nc)0.896 (0.104)0.947 (0.053)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)0.667 (0.333)0 (1)
(Ps-Ns)/(Ps+Ns)0.667 (0.333)1 (0.083)0.333 (0.75)
(Pc-Nc)/(Pc+Nc)0 (1)0.333 (0.75)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) & 0.667 (0.333) & 0 (1) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.667 (0.333) & 1 (0.083) & 0.333 (0.75) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0 (1) & 0.333 (0.75) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94399&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]0.667 (0.333)[/C][C]0 (1)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.667 (0.333)[/C][C]1 (0.083)[/C][C]0.333 (0.75)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0 (1)[/C][C]0.333 (0.75)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94399&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94399&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 (0.083)0.667 (0.333)0 (1)
(Ps-Ns)/(Ps+Ns)0.667 (0.333)1 (0.083)0.333 (0.75)
(Pc-Nc)/(Pc+Nc)0 (1)0.333 (0.75)1 (0.083)


Figures (Output of Computation)

Input Parameters & R Code

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)
}
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')