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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 computationTue, 16 Dec 2014 16:40:18 +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/16/t1418748074tafudj13yra3omk.htm/, Retrieved Thu, 31 Oct 2024 22:49:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269826, Retrieved Thu, 31 Oct 2024 22:49:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111
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] [pearson/kendall c...] [2014-10-16 21:11:53] [0f2441473984dd788bd8148394ed78a8]
- R PD        [Survey Scores] [] [2014-12-16 16:40:18] [6870495cd5e22452491bd29e9b20b7c8] [Current]
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Dataseries X:
1	1	1	1
1	2	5	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
1	1	1	1
1	1	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
1	1	1	1
1	1	1	1
1	4	1	1
2	6	2	2
1	1	1	1
1	4	1	1
2	1	1	1
2	2	2	2
1	2	1	1
1	1	1	1
3	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	4	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
3	3	1	5
1	1	1	1
1	2	1	1
2	6	2	5
1	2	1	1
2	5	2	1
1	5	1	1
1	1	1	1
1	2	1	1
2	3	2	2
1	1	1	1
2	3	1	1
1	1	1	1
1	3	1	1
1	4	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
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	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
1	1	1	1
2	2	2	2
2	2	1	1
1	1	1	1
1	1	1	1
2	2	2	1
1	1	1	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	2	1	1
1	2	1	1
1	1	1	1
1	1	1	1
2	2	2	2
2	2	2	2
2	3	1	2
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	2	1	1
1	1	1	1
1	2	1	1
1	1	1	1
1	1	1	1
1	4	1	4
1	1	1	1
1	1	1	1
1	1	1	1
1	2	1	1
2	3	1	2
2	2	1	1
1	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
2	2	1	1
2	5	1	2
1	1	1	1
1	1	1	1
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
4	4	4	4
1	1	1	4
2	1	1	1
4	1	1	1
1	2	1	1
1	2	3	2
1	5	1	1
1	2	1	1
1	1	1	1
1	1	1	1
3	3	2	3
1	2	1	1
6	7	4	5
1	1	1	1
1	1	1	1
1	2	1	1
3	5	4	4
2	1	1	1
2	2	1	1
2	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	2	1	2
1	1	1	1
2	3	2	1
1	3	2	1
1	1	1	1
3	1	1	1
1	2	1	1
2	4	1	1
2	2	2	2
1	1	1	1
3	2	1	1
1	1	1	1
4	5	1	3
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
3	2	1	1
1	1	1	2
1	1	1	1
1	2	1	1
4	5	2	1
1	1	1	1
1	1	1	1
1	1	1	1
1	2	2	2
2	4	3	4
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	1
1	1	1	1
1	1	1	1
2	2	1	1
1	2	1	1
2	2	1	1
1	4	4	4
1	1	1	1
1	2	2	2
1	2	1	1
1	1	1	1
1	1	1	1
2	2	1	1
1	2	1	1
1	1	1	1
2	1	1	1
1	1	1	1
1	2	1	1
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	1	1	1
3	2	1	2
1	1	1	1
2	2	1	1
3	4	2	3
1	2	1	1
2	3	2	2
2	5	3	2
1	1	1	1
4	4	4	4
1	1	1	1
1	3	1	1
1	1	1	1
2	1	1	1
1	1	1	2
1	1	1	1
1	1	1	1
5	2	1	1
1	1	1	1
1	1	1	1
4	3	3	2
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	3	1	1
1	1	1	1
1	2	1	1
3	3	5	3
1	1	1	1
1	1	1	1
1	1	1	1
2	2	1	1
1	1	1	1
1	2	1	1
1	1	1	1
2	1	1	1
5	5	2	5
1	1	1	1
2	1	1	1
3	2	3	2
1	2	1	1
1	1	1	1
NA	NA	NA	NA
NA	NA	NA	NA
1	2	1	1
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269826&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269826&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269826&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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)
1-2.567709-0.984263-0.97
2-2.2120625-0.9414244-0.89
3-2.76746-0.984265-0.97
4-2.687740-0.985261-0.96

\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 & -2.56 & 7 & 709 & -0.98 & 4 & 263 & -0.97 \tabularnewline
2 & -2.21 & 20 & 625 & -0.94 & 14 & 244 & -0.89 \tabularnewline
3 & -2.7 & 6 & 746 & -0.98 & 4 & 265 & -0.97 \tabularnewline
4 & -2.68 & 7 & 740 & -0.98 & 5 & 261 & -0.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269826&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]-2.56[/C][C]7[/C][C]709[/C][C]-0.98[/C][C]4[/C][C]263[/C][C]-0.97[/C][/ROW]
[ROW][C]2[/C][C]-2.21[/C][C]20[/C][C]625[/C][C]-0.94[/C][C]14[/C][C]244[/C][C]-0.89[/C][/ROW]
[ROW][C]3[/C][C]-2.7[/C][C]6[/C][C]746[/C][C]-0.98[/C][C]4[/C][C]265[/C][C]-0.97[/C][/ROW]
[ROW][C]4[/C][C]-2.68[/C][C]7[/C][C]740[/C][C]-0.98[/C][C]5[/C][C]261[/C][C]-0.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269826&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269826&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)
1-2.567709-0.984263-0.97
2-2.2120625-0.9414244-0.89
3-2.76746-0.984265-0.97
4-2.687740-0.985261-0.96







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.962 (0.038)0.942 (0.058)
(Ps-Ns)/(Ps+Ns)0.962 (0.038)1 (0)0.993 (0.007)
(Pc-Nc)/(Pc+Nc)0.942 (0.058)0.993 (0.007)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) & 0.962 (0.038) & 0.942 (0.058) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.962 (0.038) & 1 (0) & 0.993 (0.007) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.942 (0.058) & 0.993 (0.007) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269826&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]0.962 (0.038)[/C][C]0.942 (0.058)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.962 (0.038)[/C][C]1 (0)[/C][C]0.993 (0.007)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.942 (0.058)[/C][C]0.993 (0.007)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269826&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269826&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)0.962 (0.038)0.942 (0.058)
(Ps-Ns)/(Ps+Ns)0.962 (0.038)1 (0)0.993 (0.007)
(Pc-Nc)/(Pc+Nc)0.942 (0.058)0.993 (0.007)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)0.707 (0.18)0.548 (0.279)
(Ps-Ns)/(Ps+Ns)0.707 (0.18)1 (0.083)0.775 (0.157)
(Pc-Nc)/(Pc+Nc)0.548 (0.279)0.775 (0.157)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) & 0.707 (0.18) & 0.548 (0.279) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.707 (0.18) & 1 (0.083) & 0.775 (0.157) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.548 (0.279) & 0.775 (0.157) & 1 (0.056) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269826&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]0.707 (0.18)[/C][C]0.548 (0.279)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.707 (0.18)[/C][C]1 (0.083)[/C][C]0.775 (0.157)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.548 (0.279)[/C][C]0.775 (0.157)[/C][C]1 (0.056)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269826&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269826&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)0.707 (0.18)0.548 (0.279)
(Ps-Ns)/(Ps+Ns)0.707 (0.18)1 (0.083)0.775 (0.157)
(Pc-Nc)/(Pc+Nc)0.548 (0.279)0.775 (0.157)1 (0.056)



Parameters (Session):
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')