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Author's title

Author

*Unverified author*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Mon, 18 Oct 2010 21:03:57 +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/2010/Oct/18/t1287435762alry2e3rc1li0gz.htm/, Retrieved Sat, 04 May 2024 18:11:57 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=85536, Retrieved Sat, 04 May 2024 18:11:57 +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] [Score analyse A c...] [2010-10-18 21:03:57] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

2	4	3	1	4	1	2	5	2	1	1	1	3
3	3	4	2	2	5	3	7	4	2	4	1	3
7	7	7	7	8	7	7	7	9	8	4	2	1
2	6	4	7	6	9	7	6	6	7	5	5	1
2	4	3	3	8	6	2	2	2	2	5	5	3
4	3	2	2	1	2	4	4	4	3	2	5	5
4	7	10	8	9	8	5	10	10	9	6	6	3
4	4	6	7	4	7	7	7	8	8	7	6	3
3	6	6	7	4	4	4	2	7	4	7	7	3
9	9	7	9	8	6	5	6	8	8	6	7	5
5	6	6	7	8	7	6	4	6	6	7	7	5
2	2	3	4	7	2	7	2	6	7	7	7	5
3	8	8	6	8	6	5	6	6	8	7	7	5
7	8	8	7	8	7	8	6	6	6	8	7	5
3	8	8	6	8	6	7	6	6	7	7	7	5
7	8	7	7	7	8	9	8	7	6	7	7	6
4	6	5	6	6	6	6	6	7	7	7	7	6
6	6	6	6	7	6	6	6	6	6	7	7	7
2	2	4	6	8	6	2	1	7	8	8	8	2
5	10	10	10	10	8	6	10	8	8	3	8	3
7	7	8	8	8	8	7	5	7	7	7	8	3
5	6	7	6	6	6	6	6	7	6	6	8	4
4	5	6	7	6	8	6	7	5	7	8	8	5
8	8	8	8	8	8	7	7	8	8	8	8	7
7	7	6	7	8	9	6	7	9	9	8	9	2
6	6	8	10	9	7	10	6	9	9	9	9	4
8	5	6	9	10	9	7	6	9	8	9	9	6
7	7	7	6	8	7	5	6	8	7	9	9	7
3	7	8	8	7	7	8	6	6	8	9	9	7
4	7	6	7	9	9	7	8	7	8	9	9	9
5	10	6	10	8	7	7	5	5	9	9	9	9
3	5	5	8	6	5	7	3	10	9	10	10	1
5	10	4	10	3	5	4	1	8	10	6	10	3
8	9	10	7	8	7	9	8	7	8	10	10	3
5	3	5	7	7	10	10	5	10	10	10	10	3
5	8	10	7	10	10	5	7	10	10	10	10	5
5	5	6	8	4	4	6	9	8	8	10	10	6
2	2	4	2	4	6	5	1	2	5	1	10	7
8	8	6	8	7	4	7	8	9	8	9	10	8
1	6	4	7	7	5	6	8	9	8	9	10	9

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	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=85536&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=85536&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=85536&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	'George Udny Yule' @ 72.249.76.132

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	-0.75	23.5	53.5	-0.39	13	27	-0.35
2	0.7	52.5	24.5	0.36	27	13	0.35
3	0.67	48.5	21.5	0.39	27	13	0.35
4	1.2	67	19	0.56	34	6	0.7
5	1.35	72	18	0.6	32	8	0.6
6	0.95	56	18	0.51	30	10	0.5
7	0.58	43.5	20.5	0.36	27	13	0.35
8	0.25	41.5	31.5	0.14	27	13	0.35
9	1.45	72.5	14.5	0.67	33	7	0.65
10	1.58	79	16	0.66	34	6	0.7
11	1.53	80	19	0.62	32	8	0.6
12	2.05	96	14	0.75	34	6	0.7
13	-0.83	22.5	55.5	-0.42	13	27	-0.35

\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 & -0.75 & 23.5 & 53.5 & -0.39 & 13 & 27 & -0.35 \tabularnewline
2 & 0.7 & 52.5 & 24.5 & 0.36 & 27 & 13 & 0.35 \tabularnewline
3 & 0.67 & 48.5 & 21.5 & 0.39 & 27 & 13 & 0.35 \tabularnewline
4 & 1.2 & 67 & 19 & 0.56 & 34 & 6 & 0.7 \tabularnewline
5 & 1.35 & 72 & 18 & 0.6 & 32 & 8 & 0.6 \tabularnewline
6 & 0.95 & 56 & 18 & 0.51 & 30 & 10 & 0.5 \tabularnewline
7 & 0.58 & 43.5 & 20.5 & 0.36 & 27 & 13 & 0.35 \tabularnewline
8 & 0.25 & 41.5 & 31.5 & 0.14 & 27 & 13 & 0.35 \tabularnewline
9 & 1.45 & 72.5 & 14.5 & 0.67 & 33 & 7 & 0.65 \tabularnewline
10 & 1.58 & 79 & 16 & 0.66 & 34 & 6 & 0.7 \tabularnewline
11 & 1.53 & 80 & 19 & 0.62 & 32 & 8 & 0.6 \tabularnewline
12 & 2.05 & 96 & 14 & 0.75 & 34 & 6 & 0.7 \tabularnewline
13 & -0.83 & 22.5 & 55.5 & -0.42 & 13 & 27 & -0.35 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=85536&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]-0.75[/C][C]23.5[/C][C]53.5[/C][C]-0.39[/C][C]13[/C][C]27[/C][C]-0.35[/C][/ROW]
[ROW][C]2[/C][C]0.7[/C][C]52.5[/C][C]24.5[/C][C]0.36[/C][C]27[/C][C]13[/C][C]0.35[/C][/ROW]
[ROW][C]3[/C][C]0.67[/C][C]48.5[/C][C]21.5[/C][C]0.39[/C][C]27[/C][C]13[/C][C]0.35[/C][/ROW]
[ROW][C]4[/C][C]1.2[/C][C]67[/C][C]19[/C][C]0.56[/C][C]34[/C][C]6[/C][C]0.7[/C][/ROW]
[ROW][C]5[/C][C]1.35[/C][C]72[/C][C]18[/C][C]0.6[/C][C]32[/C][C]8[/C][C]0.6[/C][/ROW]
[ROW][C]6[/C][C]0.95[/C][C]56[/C][C]18[/C][C]0.51[/C][C]30[/C][C]10[/C][C]0.5[/C][/ROW]
[ROW][C]7[/C][C]0.58[/C][C]43.5[/C][C]20.5[/C][C]0.36[/C][C]27[/C][C]13[/C][C]0.35[/C][/ROW]
[ROW][C]8[/C][C]0.25[/C][C]41.5[/C][C]31.5[/C][C]0.14[/C][C]27[/C][C]13[/C][C]0.35[/C][/ROW]
[ROW][C]9[/C][C]1.45[/C][C]72.5[/C][C]14.5[/C][C]0.67[/C][C]33[/C][C]7[/C][C]0.65[/C][/ROW]
[ROW][C]10[/C][C]1.58[/C][C]79[/C][C]16[/C][C]0.66[/C][C]34[/C][C]6[/C][C]0.7[/C][/ROW]
[ROW][C]11[/C][C]1.53[/C][C]80[/C][C]19[/C][C]0.62[/C][C]32[/C][C]8[/C][C]0.6[/C][/ROW]
[ROW][C]12[/C][C]2.05[/C][C]96[/C][C]14[/C][C]0.75[/C][C]34[/C][C]6[/C][C]0.7[/C][/ROW]
[ROW][C]13[/C][C]-0.83[/C][C]22.5[/C][C]55.5[/C][C]-0.42[/C][C]13[/C][C]27[/C][C]-0.35[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=85536&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=85536&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	-0.75	23.5	53.5	-0.39	13	27	-0.35
2	0.7	52.5	24.5	0.36	27	13	0.35
3	0.67	48.5	21.5	0.39	27	13	0.35
4	1.2	67	19	0.56	34	6	0.7
5	1.35	72	18	0.6	32	8	0.6
6	0.95	56	18	0.51	30	10	0.5
7	0.58	43.5	20.5	0.36	27	13	0.35
8	0.25	41.5	31.5	0.14	27	13	0.35
9	1.45	72.5	14.5	0.67	33	7	0.65
10	1.58	79	16	0.66	34	6	0.7
11	1.53	80	19	0.62	32	8	0.6
12	2.05	96	14	0.75	34	6	0.7
13	-0.83	22.5	55.5	-0.42	13	27	-0.35

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.981 (0)	0.959 (0)
(Ps-Ns)/(Ps+Ns)	0.981 (0)	1 (0)	0.981 (0)
(Pc-Nc)/(Pc+Nc)	0.959 (0)	0.981 (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) & 0.981 (0) & 0.959 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.981 (0) & 1 (0) & 0.981 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.959 (0) & 0.981 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=85536&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]0.981 (0)[/C][C]0.959 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.981 (0)[/C][C]1 (0)[/C][C]0.981 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.959 (0)[/C][C]0.981 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=85536&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=85536&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)	0.981 (0)	0.959 (0)
(Ps-Ns)/(Ps+Ns)	0.981 (0)	1 (0)	0.981 (0)
(Pc-Nc)/(Pc+Nc)	0.959 (0)	0.981 (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)	0.916 (0)	0.816 (0)
(Ps-Ns)/(Ps+Ns)	0.916 (0)	1 (0)	0.821 (0)
(Pc-Nc)/(Pc+Nc)	0.816 (0)	0.821 (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) & 0.916 (0) & 0.816 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.916 (0) & 1 (0) & 0.821 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.816 (0) & 0.821 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=85536&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]0.916 (0)[/C][C]0.816 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.916 (0)[/C][C]1 (0)[/C][C]0.821 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.816 (0)[/C][C]0.821 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=85536&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=85536&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)	0.916 (0)	0.816 (0)
(Ps-Ns)/(Ps+Ns)	0.916 (0)	1 (0)	0.821 (0)
(Pc-Nc)/(Pc+Nc)	0.816 (0)	0.821 (0)	1 (0)

Parameters (Session):

par1 = 1 2 3 4 5 6 7 8 9 10 ;

Parameters (R input):

par1 = 1 2 3 4 5 6 7 8 9 10 ;

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