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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 computationTue, 09 Dec 2014 09:46:32 +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/09/t1418118397xs31cur5gjmdkn7.htm/, Retrieved Thu, 16 May 2024 13:09:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264364, Retrieved Thu, 16 May 2024 13:09:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

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 11:28:29] [b98453cac15ba1066b407e146608df68]
- RMP   [Survey Scores] [] [2014-10-09 22:12:20] [32b17a345b130fdf5cc88718ed94a974]
-    D      [Survey Scores] [] [2014-12-09 09:46:32] [4448df9721b6d3ffbdda9a6b78484597] [Current]
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Dataset

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

Tables (Output of Computation)





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=264364&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=264364&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264364&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 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)
1-0.22122182-0.288115-0.13
2-0.4388207-0.463128-0.34
3-0.6575257-0.5557152-0.45
4-0.16134178-0.1495110-0.07

\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 & -0.22 & 122 & 182 & -0.2 & 88 & 115 & -0.13 \tabularnewline
2 & -0.43 & 88 & 207 & -0.4 & 63 & 128 & -0.34 \tabularnewline
3 & -0.65 & 75 & 257 & -0.55 & 57 & 152 & -0.45 \tabularnewline
4 & -0.16 & 134 & 178 & -0.14 & 95 & 110 & -0.07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264364&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]-0.22[/C][C]122[/C][C]182[/C][C]-0.2[/C][C]88[/C][C]115[/C][C]-0.13[/C][/ROW]
[ROW][C]2[/C][C]-0.43[/C][C]88[/C][C]207[/C][C]-0.4[/C][C]63[/C][C]128[/C][C]-0.34[/C][/ROW]
[ROW][C]3[/C][C]-0.65[/C][C]75[/C][C]257[/C][C]-0.55[/C][C]57[/C][C]152[/C][C]-0.45[/C][/ROW]
[ROW][C]4[/C][C]-0.16[/C][C]134[/C][C]178[/C][C]-0.14[/C][C]95[/C][C]110[/C][C]-0.07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264364&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264364&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)
1-0.22122182-0.288115-0.13
2-0.4388207-0.463128-0.34
3-0.6575257-0.5557152-0.45
4-0.16134178-0.1495110-0.07






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.996 (0.004)0.987 (0.013)
(Ps-Ns)/(Ps+Ns)0.996 (0.004)1 (0)0.997 (0.003)
(Pc-Nc)/(Pc+Nc)0.987 (0.013)0.997 (0.003)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) & 0.996 (0.004) & 0.987 (0.013) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.996 (0.004) & 1 (0) & 0.997 (0.003) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.987 (0.013) & 0.997 (0.003) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264364&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]0.996 (0.004)[/C][C]0.987 (0.013)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.996 (0.004)[/C][C]1 (0)[/C][C]0.997 (0.003)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.987 (0.013)[/C][C]0.997 (0.003)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264364&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264364&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)0.996 (0.004)0.987 (0.013)
(Ps-Ns)/(Ps+Ns)0.996 (0.004)1 (0)0.997 (0.003)
(Pc-Nc)/(Pc+Nc)0.987 (0.013)0.997 (0.003)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=264364&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=264364&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264364&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)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)


Figures (Output of Computation)

Input Parameters & R Code

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')