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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 computationWed, 02 Jun 2010 08:58:02 +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/02/t12754691193gca0z9kmu1mthf.htm/, Retrieved Fri, 29 Mar 2024 07:41:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76950, Retrieved Fri, 29 Mar 2024 07:41:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [two-way anova wit...] [2010-05-26 17:02:24] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R PD  [Two-Way ANOVA] [ANOVA with good l...] [2010-05-28 23:09:47] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R       [Variability] [ANOVA with better...] [2010-05-29 09:47:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R         [Variability] [ANOVA with better...] [2010-05-29 09:54:40] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD          [T-Tests] [t-test stats exam ] [2010-06-02 08:58:02] [12ca761161c9e57b19a6283d5aac78a7] [Current]
-   P             [T-Tests] [t test ] [2010-06-02 09:14:16] [ca384074e13d8ac77eea5bf691c887ff]
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Dataseries X:
91.3	90.2
88.8	87.0
87.0	81.8
114.0	110.5
107.4	103.5
89.2	90.2
84.1	84.0
90.0	87.6
95.4	95.0
97.3	93.6
108.1	100.9
101.5	101.9
83.4	75.0
102.2	96.3
84.0	82.6
103.7	95.7
99.2	99.2
126.0	123.2
103.7	95.5
117.9	117.0
112.4	111.8
85.0	80.0
83.8	77.9
73.8	74.8
67.7	66.1
106.9	103.7
102.5	102.0
81.5	78.9
79.5	82.2
103.0	97.2
127.5	124.7
101.6	100.3
106.0	101.0
112.8	111.2
98.4	95.0
114.9	105.3
103.4	96.0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server184.73.214.54 @ 184.73.214.54

\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 & 184.73.214.54 @ 184.73.214.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76950&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]184.73.214.54 @ 184.73.214.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76950&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76950&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server184.73.214.54 @ 184.73.214.54







Wilcoxon Test
StatisticP-value
Wilcoxon Test796.50.22802

\begin{tabular}{lllllllll}
\hline
Wilcoxon Test \tabularnewline
 & Statistic & P-value \tabularnewline
Wilcoxon Test & 796.5 & 0.22802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76950&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]796.5[/C][C]0.22802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76950&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76950&T=1

As an alternative you can also use a QR Code:  

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

Wilcoxon Test
StatisticP-value
Wilcoxon Test796.50.22802







Standard Deviations
Variable 113.96823
Variable 213.56141

\begin{tabular}{lllllllll}
\hline
Standard Deviations \tabularnewline
Variable 1 & 13.96823 \tabularnewline
Variable 2 & 13.56141 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76950&T=2

[TABLE]
[ROW][C]Standard Deviations[/C][/ROW]
[ROW][C]Variable 1[/C][C]13.96823[/C][/ROW]
[ROW][C]Variable 2[/C][C]13.56141[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76950&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76950&T=2

As an alternative you can also use a QR Code:  

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

Standard Deviations
Variable 113.96823
Variable 213.56141



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