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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Thu, 04 Dec 2014 22:45:22 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/04/t1417733201e1o6t249tncnxa5.htm/, Retrieved Thu, 16 May 2024 14:31:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263450, Retrieved Thu, 16 May 2024 14:31:48 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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]
-   PD      [Survey Scores] [] [2014-12-04 22:45:22] [6993448de96b8662e47595bfdf466bf3] [Current]

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Dataseries X:

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Histogram

Boxplots

5	4	5	4	4	5
5	5	5	5	5	5
4	4	4	4	4	4
3	2	4	3	1	3
5	4	5	5	4	4
3	3	4	2	3	3
4	4	4	4	4	4
4	4	4	4	4	4
3	3	3	3	3	3
4	3	4	4	4	3
5	4	5	2	4	5
2	2	4	4	2	2
2	3	4	4	3	2
4	4	4	4	4	4
4	4	4	4	4	4
4	5	5	5	5	5
4	2	4	4	4	4
2	4	4	4	4	3
4	4	4	4	3	4
4	4	4	4	4	4
1	4	4	5	5	4
2	4	3	4	4	2
4	4	4	4	4	4
2	4	4	4	3	3
4	4	4	4	4	4
5	5	5	5	5	5
2	3	4	4	2	2
4	2	4	4	4	4
4	4	4	4	4	4
2	4	4	5	3	2
4	4	4	4	3	4
4	3	3	3	3	3
4	3	4	4	3	4
4	4	4	5	4	3
4	2	4	4	3	3
4	4	4	4	4	4
5	4	5	4	4	4
4	4	4	4	4	4
4	4	4	4	4	4
5	4	5	4	3	3
3	4	4	4	3	3
4	4	4	4	2	4
4	5	5	5	5	5
4	4	4	4	3	4
5	3	4	4	3	3
5	3	5	4	4	4
4	3	4	4	4	4
4	4	4	4	4	4
5	5	5	5	5	5
4	4	4	4	4	4
2	4	5	5	4	4
4	3	4	4	3	2
3	2	2	4	3	2
5	4	4	5	5	4
2	4	2	2	1	2
5	5	5	5	4	5
5	4	5	4	4	5
4	4	4	4	4	4
4	4	4	4	4	4
3	4	4	4	4	4
4	3	4	4	4	3
5	4	5	4	4	4
5	3	5	5	4	4
4	3	4	3	3	4
4	4	4	4	3	4
4	4	3	3	3	3
4	5	5	5	4	5
5	5	5	4	5	5
2	3	4	3	2	2
4	4	5	4	4	4
5	5	5	4	4	5
5	4	4	3	4	4
4	4	4	4	4	4
5	4	4	4	3	4
4	1	3	1	2	1
4	3	4	4	3	4
4	4	4	4	3	3
4	4	4	4	4	4
4	4	5	4	4	5
5	4	4	4	3	4
5	5	5	1	5	5
3	4	4	4	4	3
4	3	4	4	4	4
4	5	5	5	5	5
2	2	4	3	3	2
2	3	2	4	3	4
4	3	4	4	3	4
4	4	4	4	3	4
5	5	5	5	5	5
4	4	4	4	4	4
4	3	4	4	3	3
4	4	4	4	3	4
2	2	3	3	2	2
4	4	4	4	4	5
3	3	3	3	2	3
4	4	4	4	4	4
4	4	4	4	3	4
3	4	4	4	4	3
2	2	3	3	3	3
3	4	4	4	3	4
5	5	5	5	5	5
4	4	5	4	4	4
3	4	4	4	3	3
4	4	3	4	4	3
4	4	5	4	2	4
4	4	4	4	4	4
5	3	5	3	3	3
4	3	4	3	3	4
4	5	4	5	4	4
4	4	4	4	4	4
4	5	4	4	5	5

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=263450&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=263450&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263450&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.84	109	16	0.74	85	15	0.7
2	0.74	93	11	0.79	78	10	0.77
3	1.12	127	3	0.95	99	3	0.94
4	0.94	111	7	0.88	93	5	0.9
5	0.6	79	12	0.74	66	10	0.74
6	0.74	95	13	0.76	76	12	0.73

\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 & 0.84 & 109 & 16 & 0.74 & 85 & 15 & 0.7 \tabularnewline
2 & 0.74 & 93 & 11 & 0.79 & 78 & 10 & 0.77 \tabularnewline
3 & 1.12 & 127 & 3 & 0.95 & 99 & 3 & 0.94 \tabularnewline
4 & 0.94 & 111 & 7 & 0.88 & 93 & 5 & 0.9 \tabularnewline
5 & 0.6 & 79 & 12 & 0.74 & 66 & 10 & 0.74 \tabularnewline
6 & 0.74 & 95 & 13 & 0.76 & 76 & 12 & 0.73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263450&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]0.84[/C][C]109[/C][C]16[/C][C]0.74[/C][C]85[/C][C]15[/C][C]0.7[/C][/ROW]
[ROW][C]2[/C][C]0.74[/C][C]93[/C][C]11[/C][C]0.79[/C][C]78[/C][C]10[/C][C]0.77[/C][/ROW]
[ROW][C]3[/C][C]1.12[/C][C]127[/C][C]3[/C][C]0.95[/C][C]99[/C][C]3[/C][C]0.94[/C][/ROW]
[ROW][C]4[/C][C]0.94[/C][C]111[/C][C]7[/C][C]0.88[/C][C]93[/C][C]5[/C][C]0.9[/C][/ROW]
[ROW][C]5[/C][C]0.6[/C][C]79[/C][C]12[/C][C]0.74[/C][C]66[/C][C]10[/C][C]0.74[/C][/ROW]
[ROW][C]6[/C][C]0.74[/C][C]95[/C][C]13[/C][C]0.76[/C][C]76[/C][C]12[/C][C]0.73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263450&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263450&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)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.84	109	16	0.74	85	15	0.7
2	0.74	93	11	0.79	78	10	0.77
3	1.12	127	3	0.95	99	3	0.94
4	0.94	111	7	0.88	93	5	0.9
5	0.6	79	12	0.74	66	10	0.74
6	0.74	95	13	0.76	76	12	0.73

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.892 (0.017)	0.816 (0.048)
(Ps-Ns)/(Ps+Ns)	0.892 (0.017)	1 (0)	0.982 (0)
(Pc-Nc)/(Pc+Nc)	0.816 (0.048)	0.982 (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) & 0.892 (0.017) & 0.816 (0.048) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.892 (0.017) & 1 (0) & 0.982 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.816 (0.048) & 0.982 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263450&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]0.892 (0.017)[/C][C]0.816 (0.048)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.892 (0.017)[/C][C]1 (0)[/C][C]0.982 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.816 (0.048)[/C][C]0.982 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263450&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263450&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)
mean	1 (0)	0.892 (0.017)	0.816 (0.048)
(Ps-Ns)/(Ps+Ns)	0.892 (0.017)	1 (0)	0.982 (0)
(Pc-Nc)/(Pc+Nc)	0.816 (0.048)	0.982 (0)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0.006)	0.643 (0.08)	0.414 (0.251)
(Ps-Ns)/(Ps+Ns)	0.643 (0.08)	1 (0.006)	0.828 (0.022)
(Pc-Nc)/(Pc+Nc)	0.414 (0.251)	0.828 (0.022)	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 (0.006) & 0.643 (0.08) & 0.414 (0.251) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.643 (0.08) & 1 (0.006) & 0.828 (0.022) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.414 (0.251) & 0.828 (0.022) & 1 (0.003) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263450&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 (0.006)[/C][C]0.643 (0.08)[/C][C]0.414 (0.251)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.643 (0.08)[/C][C]1 (0.006)[/C][C]0.828 (0.022)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.414 (0.251)[/C][C]0.828 (0.022)[/C][C]1 (0.003)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263450&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263450&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)
mean	1 (0.006)	0.643 (0.08)	0.414 (0.251)
(Ps-Ns)/(Ps+Ns)	0.643 (0.08)	1 (0.006)	0.828 (0.022)
(Pc-Nc)/(Pc+Nc)	0.414 (0.251)	0.828 (0.022)	1 (0.003)

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code