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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 computationFri, 21 Dec 2012 10:10:25 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/21/t1356102633ws231lwmrp7nrhh.htm/, Retrieved Wed, 24 Apr 2024 12:31:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203775, Retrieved Wed, 24 Apr 2024 12:31:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [] [2012-12-21 15:04:00] [c6facf0b6ae567d6b83e1aa51c1363be]
- R  D  [Survey Scores] [] [2012-12-21 15:07:35] [c6facf0b6ae567d6b83e1aa51c1363be]
-    D      [Survey Scores] [] [2012-12-21 15:10:25] [ce0248448cbe5ad845933386ae480935] [Current]
-    D        [Survey Scores] [] [2012-12-21 15:25:13] [c6facf0b6ae567d6b83e1aa51c1363be]
-    D          [Survey Scores] [] [2012-12-21 15:27:06] [c6facf0b6ae567d6b83e1aa51c1363be]
-    D            [Survey Scores] [] [2012-12-21 15:29:46] [c6facf0b6ae567d6b83e1aa51c1363be]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6	6	4	5
4	4	3	4
6	2	5	5
4	2	2	3
2	2	2	2
5	5	5	4
1	1	1	1
6	4	5	5
3	5	4	4
4	4	3	3
3	1	1	5
2	2	5	4
4	4	3	3
3	2	2	1
5	6	6	6
3	3	3	2
3	2	2	2
6	6	6	6
1	2	1	1
1	6	4	4
1	1	1	2
5	4	5	5
2	1	1	2
3	4	3	3
3	2	2	4
5	5	6	1
5	5	6	1
1	1	1	2
2	1	2	4
3	4	4	4
5	4	4	4
3	5	4	5
5	5	4	6
3	3	3	3
2	1	1	3
4	5	3	4
3	2	1	1
3	3	3	5
6	6	6	6
6	4	3	2
3	4	4	4
3	2	2	3
4	3	3	4
4	5	4	5
2	5	3	2
2	2	2	3
3	2	2	2
2	1	1	4
5	4	4	5
5	1	2	2
6	4	3	4
3	4	4	3
3	5	4	4
2	4	2	2
5	5	4	5
2	2	2	4
4	3	3	4
4	2	2	2
1	1	1	1
6	5	4	4
2	2	1	4
3	3	3	3
4	4	4	4
3	2	1	5
4	5	4	5
3	2	1	5
6	6	6	6
4	5	4	4
5	4	4	5
3	2	2	2
4	4	5	6
3	5	5	5
3	4	3	2
6	6	5	6
6	6	5	5
2	4	4	4
2	4	4	4
6	3	3	4
5	6	5	7
1	2	3	1
2	2	4	2
5	2	2	3
3	3	3	3
3	2	3	4
4	4	5	4
6	5	5	5
4	4	4	4
2	3	3	3
4	4	4	2
4	3	3	3
2	2	2	3
4	5	5	5
3	3	3	4
6	5	4	4
4	3	3	3
4	3	3	3
3	4	2	4
3	3	4	4
3	3	3	3
4	6	6	6
2	3	3	3
2	1	1	1
3	5	5	5
3	6	5	5
4	4	3	3
4	4	3	4
2	5	3	2
5	4	4	6
5	4	1	5
4	3	5	5
4	1	2	1
3	2	3	2
4	3	2	3
4	2	3	3
5	5	5	5
4	2	3	3
5	2	2	3
3	4	3	4
2	2	1	1
1	3	3	3
5	4	5	4
5	3	4	6
3	1	1	2
4	5	4	5
4	1	1	3
5	4	4	4
5	5	6	6
3	3	3	2
4	4	3	4
6	3	3	5
4	3	4	4
5	6	6	5
4	2	1	2
4	4	2	3
5	5	4	6
4	4	3	3
3	4	2	5
3	3	2	4
6	4	5	5
5	5	5	5
2	3	2	1
4	5	4	4
3	2	2	2
3	6	4	5
5	6	4	7
3	2	2	3
3	3	3	4
4	4	3	4
5	4	4	5
5	4	5	4
5	4	2	1
5	3	2	2
3	7	5	5
4	4	2	2
4	4	4	4
3	4	4	5
4	4	4	6
4	4	4	4
3	3	3	4
2	5	4	6
4	3	2	4
4	5	4	4

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'Gertrude Mary Cox' @ cox.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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203775&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203775&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203775&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'Gertrude Mary Cox' @ cox.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)
10.69149380.5988300.49
20.54147590.4388450.32
30.27112680.2472490.19
40.7163500.5396370.44

\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 & 0.69 & 149 & 38 & 0.59 & 88 & 30 & 0.49 \tabularnewline
2 & 0.54 & 147 & 59 & 0.43 & 88 & 45 & 0.32 \tabularnewline
3 & 0.27 & 112 & 68 & 0.24 & 72 & 49 & 0.19 \tabularnewline
4 & 0.7 & 163 & 50 & 0.53 & 96 & 37 & 0.44 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203775&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]0.69[/C][C]149[/C][C]38[/C][C]0.59[/C][C]88[/C][C]30[/C][C]0.49[/C][/ROW]
[ROW][C]2[/C][C]0.54[/C][C]147[/C][C]59[/C][C]0.43[/C][C]88[/C][C]45[/C][C]0.32[/C][/ROW]
[ROW][C]3[/C][C]0.27[/C][C]112[/C][C]68[/C][C]0.24[/C][C]72[/C][C]49[/C][C]0.19[/C][/ROW]
[ROW][C]4[/C][C]0.7[/C][C]163[/C][C]50[/C][C]0.53[/C][C]96[/C][C]37[/C][C]0.44[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203775&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203775&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)
10.69149380.5988300.49
20.54147590.4388450.32
30.27112680.2472490.19
40.7163500.5396370.44






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.983 (0.017)0.971 (0.029)
(Ps-Ns)/(Ps+Ns)0.983 (0.017)1 (0)0.992 (0.008)
(Pc-Nc)/(Pc+Nc)0.971 (0.029)0.992 (0.008)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) & 0.983 (0.017) & 0.971 (0.029) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.983 (0.017) & 1 (0) & 0.992 (0.008) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.971 (0.029) & 0.992 (0.008) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203775&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]0.983 (0.017)[/C][C]0.971 (0.029)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.983 (0.017)[/C][C]1 (0)[/C][C]0.992 (0.008)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.971 (0.029)[/C][C]0.992 (0.008)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203775&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203775&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)0.983 (0.017)0.971 (0.029)
(Ps-Ns)/(Ps+Ns)0.983 (0.017)1 (0)0.992 (0.008)
(Pc-Nc)/(Pc+Nc)0.971 (0.029)0.992 (0.008)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)0.667 (0.333)
(Ps-Ns)/(Ps+Ns)0.667 (0.333)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)0.667 (0.333)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) & 0.667 (0.333) & 0.667 (0.333) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.667 (0.333) & 1 (0.083) & 1 (0.083) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.667 (0.333) & 1 (0.083) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203775&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]0.667 (0.333)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.667 (0.333)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.667 (0.333)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203775&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203775&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)0.667 (0.333)
(Ps-Ns)/(Ps+Ns)0.667 (0.333)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)0.667 (0.333)1 (0.083)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')