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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, 17 Dec 2011 09:25:42 -0500

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/2011/Dec/17/t1324131959ib80hs9hiomxq3c.htm/, Retrieved Fri, 26 Apr 2024 09:12:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156333, Retrieved Fri, 26 Apr 2024 09:12:19 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

187

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Survey Scores] [] [2011-12-17 14:25:42] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]

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Dataseries X:

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Histogram

Boxplots

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

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	'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=156333&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=156333&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156333&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	'Gertrude Mary Cox' @ cox.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	-0.8	17	131.5	-0.77	24	119	-0.66
2	-0.99	14.5	156	-0.83	19	124	-0.73
3	-0.61	18	105.5	-0.71	26	117	-0.64
4	-0.35	32.5	82	-0.43	45	98	-0.37
5	-0.23	44.5	78	-0.27	59	84	-0.17
6	0.66	113	18.5	0.72	118	25	0.65
7	-0.37	42	94.5	-0.38	52	91	-0.27

\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 & -0.8 & 17 & 131.5 & -0.77 & 24 & 119 & -0.66 \tabularnewline
2 & -0.99 & 14.5 & 156 & -0.83 & 19 & 124 & -0.73 \tabularnewline
3 & -0.61 & 18 & 105.5 & -0.71 & 26 & 117 & -0.64 \tabularnewline
4 & -0.35 & 32.5 & 82 & -0.43 & 45 & 98 & -0.37 \tabularnewline
5 & -0.23 & 44.5 & 78 & -0.27 & 59 & 84 & -0.17 \tabularnewline
6 & 0.66 & 113 & 18.5 & 0.72 & 118 & 25 & 0.65 \tabularnewline
7 & -0.37 & 42 & 94.5 & -0.38 & 52 & 91 & -0.27 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156333&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]-0.8[/C][C]17[/C][C]131.5[/C][C]-0.77[/C][C]24[/C][C]119[/C][C]-0.66[/C][/ROW]
[ROW][C]2[/C][C]-0.99[/C][C]14.5[/C][C]156[/C][C]-0.83[/C][C]19[/C][C]124[/C][C]-0.73[/C][/ROW]
[ROW][C]3[/C][C]-0.61[/C][C]18[/C][C]105.5[/C][C]-0.71[/C][C]26[/C][C]117[/C][C]-0.64[/C][/ROW]
[ROW][C]4[/C][C]-0.35[/C][C]32.5[/C][C]82[/C][C]-0.43[/C][C]45[/C][C]98[/C][C]-0.37[/C][/ROW]
[ROW][C]5[/C][C]-0.23[/C][C]44.5[/C][C]78[/C][C]-0.27[/C][C]59[/C][C]84[/C][C]-0.17[/C][/ROW]
[ROW][C]6[/C][C]0.66[/C][C]113[/C][C]18.5[/C][C]0.72[/C][C]118[/C][C]25[/C][C]0.65[/C][/ROW]
[ROW][C]7[/C][C]-0.37[/C][C]42[/C][C]94.5[/C][C]-0.38[/C][C]52[/C][C]91[/C][C]-0.27[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156333&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156333&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	-0.8	17	131.5	-0.77	24	119	-0.66
2	-0.99	14.5	156	-0.83	19	124	-0.73
3	-0.61	18	105.5	-0.71	26	117	-0.64
4	-0.35	32.5	82	-0.43	45	98	-0.37
5	-0.23	44.5	78	-0.27	59	84	-0.17
6	0.66	113	18.5	0.72	118	25	0.65
7	-0.37	42	94.5	-0.38	52	91	-0.27

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.986 (0)	0.985 (0)
(Ps-Ns)/(Ps+Ns)	0.986 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.985 (0)	0.998 (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) & 0.986 (0) & 0.985 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.986 (0) & 1 (0) & 0.998 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.985 (0) & 0.998 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156333&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]0.986 (0)[/C][C]0.985 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.986 (0)[/C][C]1 (0)[/C][C]0.998 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.985 (0)[/C][C]0.998 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156333&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156333&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)	0.986 (0)	0.985 (0)
(Ps-Ns)/(Ps+Ns)	0.986 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.985 (0)	0.998 (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)	0.905 (0.003)	0.905 (0.003)
(Ps-Ns)/(Ps+Ns)	0.905 (0.003)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	0.905 (0.003)	1 (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) & 0.905 (0.003) & 0.905 (0.003) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.905 (0.003) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.905 (0.003) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156333&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]0.905 (0.003)[/C][C]0.905 (0.003)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.905 (0.003)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.905 (0.003)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156333&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156333&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)	0.905 (0.003)	0.905 (0.003)
(Ps-Ns)/(Ps+Ns)	0.905 (0.003)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	0.905 (0.003)	1 (0)	1 (0)

Parameters (Session):

par1 = pearson ;

Parameters (R input):

par1 = 1 2 3 4 ;

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