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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 computationFri, 04 Jun 2010 18:14:50 +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/2010/Jun/04/t12756753339ukg2cal80p0bq1.htm/, Retrieved Sun, 28 Apr 2024 20:23:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77487, Retrieved Sun, 28 Apr 2024 20:23:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram and QQPlot (Reddy-Moores Data)] [Obestity data - a...] [2010-06-04 16:23:26] [74be16979710d4c4e7c6647856088456]
- RMPD  [Kolmogorov-Smirnov Test] [Obestity data - K...] [2010-06-04 17:33:55] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RM D    [Aston University Statistical Software] [Obseity data - gr...] [2010-06-04 17:42:29] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RM D      [T-Tests] [obesity weight lo...] [2010-06-04 18:00:35] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R  D          [T-Tests] [obesity data - on...] [2010-06-04 18:14:50] [a9208f4f8d3b118336aae915785f2bd9] [Current]
- RM D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [obestity data ANOVA] [2010-06-04 18:31:09] [98fd0e87c3eb04e0cc2efde01dbafab6]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-2.70	0.00
-1.00	1.80
-1.00	2.40
-0.40	2.60
0.10	2.80
0.40	2.80
0.50	3.20
0.60	3.90
0.90	5.00
1.10	5.20
1.40	5.80
1.60	5.90
1.60	7.20
3.40	7.40
3.50	8.00
3.70	8.20
5.00	8.40
5.90	9.60

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77487&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77487&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77487&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Wilcoxon Test
StatisticP-value
Wilcoxon Test500.00021

\begin{tabular}{lllllllll}
\hline
Wilcoxon Test \tabularnewline
 & Statistic & P-value \tabularnewline
Wilcoxon Test & 50 & 0.00021 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77487&T=1

[TABLE]
[ROW][C]Wilcoxon Test[/C][/ROW]
[ROW][C][/C][C]Statistic[/C][C]P-value[/C][/ROW]
[ROW][C]Wilcoxon Test[/C][C]50[/C][C]0.00021[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77487&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77487&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:

Wilcoxon Test
StatisticP-value
Wilcoxon Test500.00021






Standard Deviations
Variable 12.20987
Variable 22.72178

\begin{tabular}{lllllllll}
\hline
Standard Deviations \tabularnewline
Variable 1 & 2.20987 \tabularnewline
Variable 2 & 2.72178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77487&T=2

[TABLE]
[ROW][C]Standard Deviations[/C][/ROW]
[ROW][C]Variable 1[/C][C]2.20987[/C][/ROW]
[ROW][C]Variable 2[/C][C]2.72178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77487&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77487&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:

Standard Deviations
Variable 12.20987
Variable 22.72178


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = two.sided ; par2 = 1 ; par3 = 2 ;
Parameters (R input):
par1 = less ; par2 = 1 ; par3 = 2 ; par4 = Wilcoxon-Mann_Whitney ; par5 = unpaired ; par6 = 0.0 ; par7 = 0.95 ; par8 = FALSE ;
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]), 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=FALSE), digits=5) )
a <- table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')