FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareSurvey Scores
Date of computationSun, 20 Nov 2011 10:54:22 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/20/t1321804492uzq03nwj3barjp2.htm/, Retrieved Fri, 01 Nov 2024 00:02:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145610, Retrieved Fri, 01 Nov 2024 00:02:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

Tree of Dependent Computations

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] [Intrinsic motivat...] [2011-11-20 15:54:22] [8432dc408001a08517818ba7ac24bdb0] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7	7	7	5
5	5	5	5
6	5	4	4
4	5	5	5
5	5	5	5
6	6	6	7
7	4	7	7
6	5	5	6
6	7	7	6
6	5	5	6
5	2	4	6
5	5	6	6
4	5	4	6
6	6	6	6
6	6	7	7
5	5	6	5
3	3	4	3
7	6	6	7
3	5	6	6
5	5	6	6
3	3	4	4
5	5	5	6
2	1	2	2
6	5	6	6
3	4	5	5
6	6	6	7
6	6	6	7
5	4	5	5
5	4	5	6
7	5	5	6
6	4	6	6
5	5	6	6
5	6	5	5
4	3	4	4
4	5	6	5
6	5	5	6
5	3	5	5
5	5	5	5
7	7	7	7
5	6	5	6
5	4	5	4
6	5	7	5
5	5	5	5
6	6	7	6
7	7	6	6
5	3	3	4
5	4	4	4
5	6	6	6
6	5	5	5
2	2	4	5
4	4	4	6
4	4	6	5
6	5	5	6
3	4	4	5
6	6	6	6
6	2	5	5
5	4	5	6
6	6	6	6
1	4	6	3
5	5	6	6
7	6	5	6
4	4	5	5
5	6	5	5
6	6	5	6
4	5	4	4
6	6	5	5
6	6	6	6
5	4	6	6
5	6	5	6
3	3	5	5
5	5	5	6
6	5	6	6
5	5	6	6
6	6	6	6
6	6	6	6
4	4	4	4
4	4	4	4
6	5	5	5
7	6	6	7
4	3	3	5
5	6	7	7
6	2	5	5
6	5	6	6
5	3	6	6
3	4	5	5
7	6	6	6
6	5	6	7
4	4	4	5
4	5	6	4
5	5	5	5
3	4	4	4
7	7	7	6
6	4	6	6
6	6	6	5
4	4	4	4
5	4	5	5
6	6	6	7
5	3	5	6
6	4	4	5
6	7	7	6
4	5	6	6
5	5	5	5
6	6	6	6
5	5	6	6
5	5	5	5
4	4	5	5
4	5	5	4
6	6	5	7
5	5	7	7
6	5	6	5
5	4	7	7
6	4	6	6
5	5	5	5
4	5	4	5
6	6	6	7
4	5	4	5
5	3	3	5
5	5	5	5
6	3	5	5
3	4	5	3
5	4	5	5
4	5	5	5
5	2	5	4
5	5	3	4
7	7	7	7
5	6	6	6
7	6	6	6
5	5	4	6
4	4	4	5
6	6	6	5
4	3	4	5
4	7	6	6
4	3	2	2
4	4	5	5
6	6	5	7
6	5	6	6
5	6	5	5
3	4	4	5
6	6	6	6
5	6	6	6
4	4	5	5
5	5	5	5
2	3	2	2
5	6	6	7
7	5	6	7
4	6	5	5
4	5	6	6
7	6	7	5
6	5	5	6
5	6	5	5
5	5	5	6
5	5	6	6
7	6	7	7
6	5	7	6
6	6	6	6
5	5	5	6
2	4	6	6
4	4	4	4
6	4	6	6
5	5	6	4
5	4	4	5
5	5	5	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145610&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145610&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145610&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.08196210.81118150.77
20.84163270.72106200.68
31.28218100.9113070.9
41.4424290.9313960.92

\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 & 1.08 & 196 & 21 & 0.81 & 118 & 15 & 0.77 \tabularnewline
2 & 0.84 & 163 & 27 & 0.72 & 106 & 20 & 0.68 \tabularnewline
3 & 1.28 & 218 & 10 & 0.91 & 130 & 7 & 0.9 \tabularnewline
4 & 1.44 & 242 & 9 & 0.93 & 139 & 6 & 0.92 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145610&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]1.08[/C][C]196[/C][C]21[/C][C]0.81[/C][C]118[/C][C]15[/C][C]0.77[/C][/ROW]
[ROW][C]2[/C][C]0.84[/C][C]163[/C][C]27[/C][C]0.72[/C][C]106[/C][C]20[/C][C]0.68[/C][/ROW]
[ROW][C]3[/C][C]1.28[/C][C]218[/C][C]10[/C][C]0.91[/C][C]130[/C][C]7[/C][C]0.9[/C][/ROW]
[ROW][C]4[/C][C]1.44[/C][C]242[/C][C]9[/C][C]0.93[/C][C]139[/C][C]6[/C][C]0.92[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145610&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145610&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.08196210.81118150.77
20.84163270.72106200.68
31.28218100.9113070.9
41.4424290.9313960.92






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.985 (0.015)0.981 (0.019)
(Ps-Ns)/(Ps+Ns)0.985 (0.015)1 (0)0.998 (0.002)
(Pc-Nc)/(Pc+Nc)0.981 (0.019)0.998 (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) & 0.985 (0.015) & 0.981 (0.019) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.985 (0.015) & 1 (0) & 0.998 (0.002) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.981 (0.019) & 0.998 (0.002) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145610&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]0.985 (0.015)[/C][C]0.981 (0.019)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.985 (0.015)[/C][C]1 (0)[/C][C]0.998 (0.002)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.981 (0.019)[/C][C]0.998 (0.002)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145610&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145610&T=2

As an alternative you can also use a QR Code:  
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)
mean1 (0)0.985 (0.015)0.981 (0.019)
(Ps-Ns)/(Ps+Ns)0.985 (0.015)1 (0)0.998 (0.002)
(Pc-Nc)/(Pc+Nc)0.981 (0.019)0.998 (0.002)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)

\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 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145610&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 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145610&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145610&T=3

As an alternative you can also use a QR Code:  
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)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 6 7 ;
Parameters (R input):
par1 = 1 2 3 4 5 6 7 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')