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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, 24 Dec 2010 15:27:41 +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/Dec/24/t1293204397xm5c8h3ysgmtyqa.htm/, Retrieved Tue, 30 Apr 2024 04:58:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115117, Retrieved Tue, 30 Apr 2024 04:58:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148

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 11:23:25] [b98453cac15ba1066b407e146608df68]
- R PD  [Survey Scores] [p_Stress_SC1Dep] [2010-12-04 10:08:25] [19f9551d4d95750ef21e9f3cf8fe2131]
-    D    [Survey Scores] [p_stress_SC2Dep] [2010-12-20 22:30:56] [19f9551d4d95750ef21e9f3cf8fe2131]
-    D        [Survey Scores] [Survey scores dep...] [2010-12-24 15:27:41] [0dbff7218d83c9f93b81320e51e185be] [Current]
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Dataset

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

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115117&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115117&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115117&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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)
1-1.512247-0.982148-0.97
2-1.732282-0.992156-0.97
3-1.342219-0.982145-0.97
4-1.143188-0.973126-0.95
5-1.027173-0.927122-0.89
6-0.381981-0.621781-0.65
7-0.9514168-0.8514111-0.78

\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 & -1.51 & 2 & 247 & -0.98 & 2 & 148 & -0.97 \tabularnewline
2 & -1.73 & 2 & 282 & -0.99 & 2 & 156 & -0.97 \tabularnewline
3 & -1.34 & 2 & 219 & -0.98 & 2 & 145 & -0.97 \tabularnewline
4 & -1.14 & 3 & 188 & -0.97 & 3 & 126 & -0.95 \tabularnewline
5 & -1.02 & 7 & 173 & -0.92 & 7 & 122 & -0.89 \tabularnewline
6 & -0.38 & 19 & 81 & -0.62 & 17 & 81 & -0.65 \tabularnewline
7 & -0.95 & 14 & 168 & -0.85 & 14 & 111 & -0.78 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115117&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]-1.51[/C][C]2[/C][C]247[/C][C]-0.98[/C][C]2[/C][C]148[/C][C]-0.97[/C][/ROW]
[ROW][C]2[/C][C]-1.73[/C][C]2[/C][C]282[/C][C]-0.99[/C][C]2[/C][C]156[/C][C]-0.97[/C][/ROW]
[ROW][C]3[/C][C]-1.34[/C][C]2[/C][C]219[/C][C]-0.98[/C][C]2[/C][C]145[/C][C]-0.97[/C][/ROW]
[ROW][C]4[/C][C]-1.14[/C][C]3[/C][C]188[/C][C]-0.97[/C][C]3[/C][C]126[/C][C]-0.95[/C][/ROW]
[ROW][C]5[/C][C]-1.02[/C][C]7[/C][C]173[/C][C]-0.92[/C][C]7[/C][C]122[/C][C]-0.89[/C][/ROW]
[ROW][C]6[/C][C]-0.38[/C][C]19[/C][C]81[/C][C]-0.62[/C][C]17[/C][C]81[/C][C]-0.65[/C][/ROW]
[ROW][C]7[/C][C]-0.95[/C][C]14[/C][C]168[/C][C]-0.85[/C][C]14[/C][C]111[/C][C]-0.78[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115117&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115117&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)
1-1.512247-0.982148-0.97
2-1.732282-0.992156-0.97
3-1.342219-0.982145-0.97
4-1.143188-0.973126-0.95
5-1.027173-0.927122-0.89
6-0.381981-0.621781-0.65
7-0.9514168-0.8514111-0.78






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.907 (0.005)0.911 (0.004)
(Ps-Ns)/(Ps+Ns)0.907 (0.005)1 (0)0.976 (0)
(Pc-Nc)/(Pc+Nc)0.911 (0.004)0.976 (0)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) & 0.907 (0.005) & 0.911 (0.004) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.907 (0.005) & 1 (0) & 0.976 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.911 (0.004) & 0.976 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115117&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]0.907 (0.005)[/C][C]0.911 (0.004)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.907 (0.005)[/C][C]1 (0)[/C][C]0.976 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.911 (0.004)[/C][C]0.976 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115117&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115117&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)0.907 (0.005)0.911 (0.004)
(Ps-Ns)/(Ps+Ns)0.907 (0.005)1 (0)0.976 (0)
(Pc-Nc)/(Pc+Nc)0.911 (0.004)0.976 (0)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.976 (0.002)0.926 (0.005)
(Ps-Ns)/(Ps+Ns)0.976 (0.002)1 (0.002)0.949 (0.004)
(Pc-Nc)/(Pc+Nc)0.926 (0.005)0.949 (0.004)1 (0.003)

\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) & 0.976 (0.002) & 0.926 (0.005) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.976 (0.002) & 1 (0.002) & 0.949 (0.004) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.926 (0.005) & 0.949 (0.004) & 1 (0.003) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115117&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)[/C][C]0.976 (0.002)[/C][C]0.926 (0.005)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.976 (0.002)[/C][C]1 (0.002)[/C][C]0.949 (0.004)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.926 (0.005)[/C][C]0.949 (0.004)[/C][C]1 (0.003)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115117&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115117&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)0.976 (0.002)0.926 (0.005)
(Ps-Ns)/(Ps+Ns)0.976 (0.002)1 (0.002)0.949 (0.004)
(Pc-Nc)/(Pc+Nc)0.926 (0.005)0.949 (0.004)1 (0.003)


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')