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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

Sat, 06 Dec 2014 16:45:13 +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/06/t1417884337rb2x9t2y3escnl0.htm/, Retrieved Tue, 28 May 2024 15:24:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263654, Retrieved Tue, 28 May 2024 15:24:03 +0000

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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]
- R PD  [Survey Scores] [] [2011-10-18 12:18:26] [b98453cac15ba1066b407e146608df68]
- RM      [Survey Scores] [] [2014-10-16 13:19:13] [4c4ebb0b36a379d1d949ba77427e658a]
-   PD        [Survey Scores] [] [2014-12-06 16:45:13] [d9810f96fa2f1581f787e7f797109997] [Current]

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263654&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263654&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263654&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	0 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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	-0.1	25	31	-0.11	20	27	-0.15
2	0.77	58	10	0.71	47	10	0.65
3	0.4	38	13	0.49	28	13	0.37
4	0.68	48	6	0.78	42	6	0.75
5	-0.24	23	38	-0.25	20	28	-0.17
6	-0.02	25	26	-0.02	22	25	-0.06
7	-0.95	5	64	-0.86	5	47	-0.81
8	0.18	35	24	0.19	28	19	0.19
9	0.32	35	15	0.4	32	13	0.42

\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 & -0.1 & 25 & 31 & -0.11 & 20 & 27 & -0.15 \tabularnewline
2 & 0.77 & 58 & 10 & 0.71 & 47 & 10 & 0.65 \tabularnewline
3 & 0.4 & 38 & 13 & 0.49 & 28 & 13 & 0.37 \tabularnewline
4 & 0.68 & 48 & 6 & 0.78 & 42 & 6 & 0.75 \tabularnewline
5 & -0.24 & 23 & 38 & -0.25 & 20 & 28 & -0.17 \tabularnewline
6 & -0.02 & 25 & 26 & -0.02 & 22 & 25 & -0.06 \tabularnewline
7 & -0.95 & 5 & 64 & -0.86 & 5 & 47 & -0.81 \tabularnewline
8 & 0.18 & 35 & 24 & 0.19 & 28 & 19 & 0.19 \tabularnewline
9 & 0.32 & 35 & 15 & 0.4 & 32 & 13 & 0.42 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263654&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]-0.1[/C][C]25[/C][C]31[/C][C]-0.11[/C][C]20[/C][C]27[/C][C]-0.15[/C][/ROW]
[ROW][C]2[/C][C]0.77[/C][C]58[/C][C]10[/C][C]0.71[/C][C]47[/C][C]10[/C][C]0.65[/C][/ROW]
[ROW][C]3[/C][C]0.4[/C][C]38[/C][C]13[/C][C]0.49[/C][C]28[/C][C]13[/C][C]0.37[/C][/ROW]
[ROW][C]4[/C][C]0.68[/C][C]48[/C][C]6[/C][C]0.78[/C][C]42[/C][C]6[/C][C]0.75[/C][/ROW]
[ROW][C]5[/C][C]-0.24[/C][C]23[/C][C]38[/C][C]-0.25[/C][C]20[/C][C]28[/C][C]-0.17[/C][/ROW]
[ROW][C]6[/C][C]-0.02[/C][C]25[/C][C]26[/C][C]-0.02[/C][C]22[/C][C]25[/C][C]-0.06[/C][/ROW]
[ROW][C]7[/C][C]-0.95[/C][C]5[/C][C]64[/C][C]-0.86[/C][C]5[/C][C]47[/C][C]-0.81[/C][/ROW]
[ROW][C]8[/C][C]0.18[/C][C]35[/C][C]24[/C][C]0.19[/C][C]28[/C][C]19[/C][C]0.19[/C][/ROW]
[ROW][C]9[/C][C]0.32[/C][C]35[/C][C]15[/C][C]0.4[/C][C]32[/C][C]13[/C][C]0.42[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263654&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263654&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	-0.1	25	31	-0.11	20	27	-0.15
2	0.77	58	10	0.71	47	10	0.65
3	0.4	38	13	0.49	28	13	0.37
4	0.68	48	6	0.78	42	6	0.75
5	-0.24	23	38	-0.25	20	28	-0.17
6	-0.02	25	26	-0.02	22	25	-0.06
7	-0.95	5	64	-0.86	5	47	-0.81
8	0.18	35	24	0.19	28	19	0.19
9	0.32	35	15	0.4	32	13	0.42

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.994 (0)	0.989 (0)
(Ps-Ns)/(Ps+Ns)	0.994 (0)	1 (0)	0.995 (0)
(Pc-Nc)/(Pc+Nc)	0.989 (0)	0.995 (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) & 0.994 (0) & 0.989 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.994 (0) & 1 (0) & 0.995 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.989 (0) & 0.995 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263654&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]0.994 (0)[/C][C]0.989 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.994 (0)[/C][C]1 (0)[/C][C]0.995 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.989 (0)[/C][C]0.995 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263654&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263654&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)	0.994 (0)	0.989 (0)
(Ps-Ns)/(Ps+Ns)	0.994 (0)	1 (0)	0.995 (0)
(Pc-Nc)/(Pc+Nc)	0.989 (0)	0.995 (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)	0.944 (0)	0.889 (0)
(Ps-Ns)/(Ps+Ns)	0.944 (0)	1 (0)	0.944 (0)
(Pc-Nc)/(Pc+Nc)	0.889 (0)	0.944 (0)	1 (0)

\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) & 0.944 (0) & 0.889 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.944 (0) & 1 (0) & 0.944 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.889 (0) & 0.944 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263654&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]0.944 (0)[/C][C]0.889 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.944 (0)[/C][C]1 (0)[/C][C]0.944 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.889 (0)[/C][C]0.944 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263654&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263654&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)	0.944 (0)	0.889 (0)
(Ps-Ns)/(Ps+Ns)	0.944 (0)	1 (0)	0.944 (0)
(Pc-Nc)/(Pc+Nc)	0.889 (0)	0.944 (0)	1 (0)

Parameters (Session):

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