Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

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

Tue, 16 Dec 2014 11:11:44 +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/16/t1418728379p4gn0i3ogjqzckj.htm/, Retrieved Thu, 16 May 2024 14:33:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269325, Retrieved Thu, 16 May 2024 14:33:22 +0000

QR Codes:

Paste this QR Code to cite your computation.

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] [Doubting over act...] [2014-12-16 11:11:44] [ecc8a223a6799628ce1dc096d32923a0] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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

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 Maurice George Kendall' @ kendall.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 Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269325&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269325&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269325&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 Maurice George Kendall' @ kendall.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	1.18	137.5	7	0.9	97	14	0.75
2	-0.24	30	56.5	-0.31	36	75	-0.35
3	0.64	92.5	21	0.63	75	36	0.35
4	0.15	57.5	41	0.17	47	64	-0.15
5	0.22	58.5	34	0.26	57	54	0.03
6	0.37	70.5	29	0.42	61	50	0.1

\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 & 1.18 & 137.5 & 7 & 0.9 & 97 & 14 & 0.75 \tabularnewline
2 & -0.24 & 30 & 56.5 & -0.31 & 36 & 75 & -0.35 \tabularnewline
3 & 0.64 & 92.5 & 21 & 0.63 & 75 & 36 & 0.35 \tabularnewline
4 & 0.15 & 57.5 & 41 & 0.17 & 47 & 64 & -0.15 \tabularnewline
5 & 0.22 & 58.5 & 34 & 0.26 & 57 & 54 & 0.03 \tabularnewline
6 & 0.37 & 70.5 & 29 & 0.42 & 61 & 50 & 0.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269325&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]1.18[/C][C]137.5[/C][C]7[/C][C]0.9[/C][C]97[/C][C]14[/C][C]0.75[/C][/ROW]
[ROW][C]2[/C][C]-0.24[/C][C]30[/C][C]56.5[/C][C]-0.31[/C][C]36[/C][C]75[/C][C]-0.35[/C][/ROW]
[ROW][C]3[/C][C]0.64[/C][C]92.5[/C][C]21[/C][C]0.63[/C][C]75[/C][C]36[/C][C]0.35[/C][/ROW]
[ROW][C]4[/C][C]0.15[/C][C]57.5[/C][C]41[/C][C]0.17[/C][C]47[/C][C]64[/C][C]-0.15[/C][/ROW]
[ROW][C]5[/C][C]0.22[/C][C]58.5[/C][C]34[/C][C]0.26[/C][C]57[/C][C]54[/C][C]0.03[/C][/ROW]
[ROW][C]6[/C][C]0.37[/C][C]70.5[/C][C]29[/C][C]0.42[/C][C]61[/C][C]50[/C][C]0.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269325&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269325&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	1.18	137.5	7	0.9	97	14	0.75
2	-0.24	30	56.5	-0.31	36	75	-0.35
3	0.64	92.5	21	0.63	75	36	0.35
4	0.15	57.5	41	0.17	47	64	-0.15
5	0.22	58.5	34	0.26	57	54	0.03
6	0.37	70.5	29	0.42	61	50	0.1

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.973 (0.001)	0.993 (0)
(Ps-Ns)/(Ps+Ns)	0.973 (0.001)	1 (0)	0.964 (0.002)
(Pc-Nc)/(Pc+Nc)	0.993 (0)	0.964 (0.002)	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) & 0.973 (0.001) & 0.993 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.973 (0.001) & 1 (0) & 0.964 (0.002) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.993 (0) & 0.964 (0.002) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269325&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]0.973 (0.001)[/C][C]0.993 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.973 (0.001)[/C][C]1 (0)[/C][C]0.964 (0.002)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.993 (0)[/C][C]0.964 (0.002)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269325&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269325&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)	0.973 (0.001)	0.993 (0)
(Ps-Ns)/(Ps+Ns)	0.973 (0.001)	1 (0)	0.964 (0.002)
(Pc-Nc)/(Pc+Nc)	0.993 (0)	0.964 (0.002)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0.003)	1 (0.003)	1 (0.003)
(Ps-Ns)/(Ps+Ns)	1 (0.003)	1 (0.003)	1 (0.003)
(Pc-Nc)/(Pc+Nc)	1 (0.003)	1 (0.003)	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 (0.003) & 1 (0.003) & 1 (0.003) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.003) & 1 (0.003) & 1 (0.003) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0.003) & 1 (0.003) & 1 (0.003) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269325&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 (0.003)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269325&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269325&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 (0.003)	1 (0.003)	1 (0.003)
(Ps-Ns)/(Ps+Ns)	1 (0.003)	1 (0.003)	1 (0.003)
(Pc-Nc)/(Pc+Nc)	1 (0.003)	1 (0.003)	1 (0.003)

Parameters (Session):

Parameters (R input):

par1 = 0 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