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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Tests to Compare Two Means.wasp
Title produced by softwareT-Tests
Date of computationThu, 11 Dec 2014 12:16:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/11/t1418300205yrexh437n9wlwe2.htm/, Retrieved Thu, 16 May 2024 06:02:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265833, Retrieved Thu, 16 May 2024 06:02:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [Bullying by Gender] [2009-11-23 19:30:44] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Chi Square Measure of Association- Free Statistics Software (Calculator)] [Bullying by Gende...] [2009-11-24 18:28:32] [b98453cac15ba1066b407e146608df68]
- R       [Chi Square Measure of Association- Free Statistics Software (Calculator)] [STARS Bullying Study] [2009-11-25 00:02:16] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD      [Chi-Square Test] [STARS Bullying Study] [2010-11-15 17:05:23] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R           [Chi-Square Test] [STARS Bullying Data] [2010-11-16 14:40:36] [98fd0e87c3eb04e0cc2efde01dbafab6]
-  MP           [Chi-Square Test] [chi2 Example - Ty...] [2011-11-14 11:58:51] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMP             [Chi-Square Test] [] [2014-12-11 10:55:30] [c21326623a6a7a02c714571d3353577f]
-   P               [Chi-Square Test] [] [2014-12-11 11:04:18] [c21326623a6a7a02c714571d3353577f]
-   P                 [Chi-Square Test] [] [2014-12-11 11:07:32] [c21326623a6a7a02c714571d3353577f]
- RMP                     [T-Tests] [] [2014-12-11 12:16:36] [420bed74a84f82b65a9b71ac0847dc23] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'g'	'Often'	'Both'	'Same'	'Boys'
'g'	'Not_bul'	'Physical'	'Same'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Rarely'	'Mental'	'Differnt'	'Boys'
'b'	'Not_bul'	'Physical'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Physical'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Same'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Both'	'Boys'
'g'	'Often'	'Mental'	'Same'	'Both'
'b'	'Often'	'Both'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Both'	'Both'	'Boys'
'b'	'Not_bul'	'Mental'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Not_bul'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Same'	'Boys'
'g'	'Often'	'Mental'	'Differnt'	'Girls'
'b'	'Often'	'Both'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Mental'	'Not_bul'	'Boys'
'b'	'Rarely'	'Both'	'Differnt'	'Boys'
'b'	'Often'	'Both'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Both'	'Same'	'Both'
'g'	'Often'	'Mental'	'Differnt'	'Both'
'b'	'Often'	'Both'	'Differnt'	'Both'
'g'	'Rarely'	'Physical'	'Differnt'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Differnt'	'Boys'
'g'	'Often'	'Mental'	'Differnt'	'Both'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Both'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Differnt'	'Girls'
'g'	'Often'	'Both'	'Differnt'	'Both'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Both'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Not_bul'	'Same'	'Boys'
'g'	'Often'	'Mental'	'Both'	'Girls'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Often'	'Both'	'Differnt'	'Boys'
'b'	'Rarely'	'Both'	'Differnt'	'Boys'
'g'	'Rarely'	'Not_bul'	'Not_bul'	'Girls'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Often'	'Mental'	'Same'	'Boys'
'b'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Often'	'Physical'	'Same'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Both'	'Both'	'Both'
'g'	'Rarely'	'Mental'	'Both'	'Both'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'b'	'Rarely'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Both'
'g'	'Not_bul'	'Mental'	'Same'	'Both'
'g'	'Often'	'Physical'	'Differnt'	'Both'
'b'	'Often'	'Not_bul'	'Same'	'Boys'
'b'	'Often'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Mental'	'Same'	'Not_bul'
'b'	'Often'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'g'	'Often'	'Mental'	'Same'	'Girls'
'g'	'Often'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Not_bul'	'Both'
'g'	'Often'	'Both'	'Both'	'Girls'
'g'	'Often'	'Mental'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Often'	'Mental'	'Both'	'Boys'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Physical'	'Differnt'	'Boys'
'g'	'Often'	'Both'	'Same'	'Girls'
'g'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Often'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Both'	'Both'	'Boys'
'b'	'Often'	'Not_bul'	'Both'	'Boys'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Not_bul'	'Both'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Both'	'Both'	'Boys'
'b'	'Rarely'	'Both'	'Both'	'Boys'
'b'	'Often'	'Physical'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'g'	'Often'	'Mental'	'Same'	'Girls'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'g'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Rarely'	'Both'	'Both'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Same'	'Girls'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'g'	'Often'	'Mental'	'Both'	'Both'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Both'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Mental'	'Both'	'Boys'
'g'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Often'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Same'	'Girls'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Both'	'Same'	'Boys'
'g'	'Often'	'Both'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Both'	'Same'	'Boys'
'b'	'Often'	'Mental'	'Both'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Same'	'Boys'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Often'	'Mental'	'Differnt'	'Boys'
'g'	'Often'	'Both'	'Both'	'Boys'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Often'	'Mental'	'Not_bul'	'Both'
'b'	'Rarely'	'Physical'	'Same'	'Boys'
'b'	'Often'	'Mental'	'Not_bul'	'Both'
'g'	'Rarely'	'Mental'	'Same'	'Boys'
'g'	'Often'	'Not_bul'	'Same'	'Both'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Rarely'	'Both'	'Both'	'Both'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Rarely'	'Mental'	'Differnt'	'Boys'
'b'	'Rarely'	'Mental'	'Differnt'	'Boys'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'b'	'Rarely'	'Physical'	'Differnt'	'Boys'
'g'	'Not_bul'	'Mental'	'Not_bul'	'Not_bul'
'g'	'Often'	'Both'	'Same'	'Both'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'g'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'
'b'	'Not_bul'	'Not_bul'	'Not_bul'	'Not_bul'

Tables (Output of Computation)





\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Engine error message & 
Error in plot.window(xlim = xlim, ylim = ylim, log = log, yaxs = pars$yaxs) : 
  need finite 'ylim' values
Calls: boxplot ... boxplot -> boxplot.default -> do.call -> bxp -> plot.window
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
Execution halted

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265833&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in plot.window(xlim = xlim, ylim = ylim, log = log, yaxs = pars$yaxs) : 
  need finite 'ylim' values
Calls: boxplot ... boxplot -> boxplot.default -> do.call -> bxp -> plot.window
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
Execution halted

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265833&T=0


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = two.sided ; par2 = ; par3 = ; par4 = T-Test ; par5 = unpaired ; par6 = ; par7 = ; par8 = TRUE ;
R code (references can be found in the software module):
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.character(par4)
par5 <- as.character(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
par8 <- as.logical(par8)
if ( par5 == 'unpaired') paired <- FALSE else paired <- TRUE
x <- t(y)
if(par8){
bitmap(file='test1.png')
(r<-boxplot(x ,xlab=xlab,ylab=ylab,main=main,notch=FALSE,col=2))
dev.off()
}
load(file='createtable')
if( par4 == 'Wilcoxon-Mann_Whitney'){
a<-table.start()
a <- table.row.start(a)
a <- table.element(a,'Wilcoxon Test',3,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'',1,TRUE)
a <- table.element(a,'Statistic',1,TRUE)
a <- table.element(a,'P-value',1,TRUE)
a <- table.row.end(a)
W <- wilcox.test(x[,par2],x[,par3],alternative=par1, paired = paired)
a<-table.row.start(a)
a<-table.element(a,'Wilcoxon Test',1,TRUE)
a<-table.element(a,W$statistic[[1]])
a<-table.element(a,round(W$p.value, digits=5) )
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if( par4 == 'T-Test')
{
T <- t.test(x[,par2],x[,par3],alternative=par1, paired=paired, mu=par6, conf.level=par7)
a<-table.start()
a <- table.row.start(a)
a <- table.element(a,'T-Test',3,TRUE)
a <- table.row.end(a)
if(paired){
a <- table.row.start(a)
a <- table.element(a,'Difference: Mean1 - Mean2',1,TRUE)
a<-table.element(a,round(T$estimate, digits=5) )
a <- table.row.end(a)
}
if(!paired){
a <- table.row.start(a)
a <- table.element(a,'Mean1',1,TRUE)
a<-table.element(a,round(T$estimate[1], digits=5) )
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Mean2',1,TRUE)
a<-table.element(a,round(T$estimate[2], digits=5) )
a <- table.row.end(a)
}
a <- table.row.start(a)
a <- table.element(a,'T Statistic',1,TRUE)
a<-table.element(a,round(T$statistic, digits=5) )
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'P-value',1,TRUE)
a<-table.element(a,round(T$p.value, digits=5) )
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Lower Confidence Limit',1,TRUE)
a<-table.element(a,round(T$conf.int[1], digits=5) )
a <- table.row.end(a)
a<-table.row.start(a)
a <- table.element(a,'Upper Confidence Limit',1,TRUE)
a<-table.element(a,round(T$conf.int[2], digits=5) )
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,'Standard Deviations',3,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Variable 1',1,TRUE)
a<-table.element(a,round(sd(x[,par2], na.rm=TRUE), digits=5) )
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Variable 2',1,TRUE)
a<-table.element(a,round(sd(x[,par3], na.rm=TRUE), digits=5) )
a <- table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')