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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, 02 Dec 2014 19:20:20 +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/02/t1417548035e8mdo9a9xg9l79b.htm/, Retrieved Thu, 16 May 2024 18:16:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=262867, Retrieved Thu, 16 May 2024 18:16:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [] [2014-12-02 19:03:09] [3cc57788b191749bdc089f5fad42e0f8]
-    D    [Survey Scores] [] [2014-12-02 19:20:20] [afff6d6b458ee8576605d3685f592a9b] [Current]
- R P       [Survey Scores] [] [2014-12-06 13:39:04] [3cc57788b191749bdc089f5fad42e0f8]
- RMPD      [Notched Boxplots] [] [2014-12-06 13:58:21] [3cc57788b191749bdc089f5fad42e0f8]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262867&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262867&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262867&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 time1 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)
1-1.4326426-0.8814247-0.89
2-1.1361375-0.7236221-0.72
3-1.5721460-0.9113254-0.9
4-1.6123472-0.9115256-0.89

\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 & -1.43 & 26 & 426 & -0.88 & 14 & 247 & -0.89 \tabularnewline
2 & -1.13 & 61 & 375 & -0.72 & 36 & 221 & -0.72 \tabularnewline
3 & -1.57 & 21 & 460 & -0.91 & 13 & 254 & -0.9 \tabularnewline
4 & -1.61 & 23 & 472 & -0.91 & 15 & 256 & -0.89 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262867&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]-1.43[/C][C]26[/C][C]426[/C][C]-0.88[/C][C]14[/C][C]247[/C][C]-0.89[/C][/ROW]
[ROW][C]2[/C][C]-1.13[/C][C]61[/C][C]375[/C][C]-0.72[/C][C]36[/C][C]221[/C][C]-0.72[/C][/ROW]
[ROW][C]3[/C][C]-1.57[/C][C]21[/C][C]460[/C][C]-0.91[/C][C]13[/C][C]254[/C][C]-0.9[/C][/ROW]
[ROW][C]4[/C][C]-1.61[/C][C]23[/C][C]472[/C][C]-0.91[/C][C]15[/C][C]256[/C][C]-0.89[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262867&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262867&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)
1-1.4326426-0.8814247-0.89
2-1.1361375-0.7236221-0.72
3-1.5721460-0.9113254-0.9
4-1.6123472-0.9115256-0.89






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.977 (0.023)0.939 (0.061)
(Ps-Ns)/(Ps+Ns)0.977 (0.023)1 (0)0.991 (0.009)
(Pc-Nc)/(Pc+Nc)0.939 (0.061)0.991 (0.009)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) & 0.977 (0.023) & 0.939 (0.061) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.977 (0.023) & 1 (0) & 0.991 (0.009) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.939 (0.061) & 0.991 (0.009) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262867&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]0.977 (0.023)[/C][C]0.939 (0.061)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.977 (0.023)[/C][C]1 (0)[/C][C]0.991 (0.009)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.939 (0.061)[/C][C]0.991 (0.009)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262867&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262867&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)0.977 (0.023)0.939 (0.061)
(Ps-Ns)/(Ps+Ns)0.977 (0.023)1 (0)0.991 (0.009)
(Pc-Nc)/(Pc+Nc)0.939 (0.061)0.991 (0.009)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)0.913 (0.071)0.548 (0.279)
(Ps-Ns)/(Ps+Ns)0.913 (0.071)1 (0.056)0.8 (0.126)
(Pc-Nc)/(Pc+Nc)0.548 (0.279)0.8 (0.126)1 (0.056)

\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) & 0.913 (0.071) & 0.548 (0.279) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.913 (0.071) & 1 (0.056) & 0.8 (0.126) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.548 (0.279) & 0.8 (0.126) & 1 (0.056) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262867&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]0.913 (0.071)[/C][C]0.548 (0.279)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.913 (0.071)[/C][C]1 (0.056)[/C][C]0.8 (0.126)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.548 (0.279)[/C][C]0.8 (0.126)[/C][C]1 (0.056)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262867&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262867&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)0.913 (0.071)0.548 (0.279)
(Ps-Ns)/(Ps+Ns)0.913 (0.071)1 (0.056)0.8 (0.126)
(Pc-Nc)/(Pc+Nc)0.548 (0.279)0.8 (0.126)1 (0.056)


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')