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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 computationFri, 01 Jun 2012 06:25:25 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jun/01/t13385463325418fgajxfwkmmn.htm/, Retrieved Thu, 02 May 2024 04:27:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168676, Retrieved Thu, 02 May 2024 04:27:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Simple Linear Regression] [Triglyceridge Reg...] [2011-07-07 15:11:49] [74be16979710d4c4e7c6647856088456]
- R     [Simple Linear Regression] [Triglyceride] [2012-05-04 19:33:41] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R       [Simple Linear Regression] [influence of leve...] [2012-06-01 08:56:32] [c14255f5a914c4d7aab5f6cd60318f9b]
- RMPD      [CARE Data - Boxplots and Scatterplot Matrix] [] [2012-06-01 10:12:53] [c14255f5a914c4d7aab5f6cd60318f9b]
- RM D          [T-Tests] [] [2012-06-01 10:25:25] [0507bbe3d00274d9f4e781e2396a3b5a] [Current]
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Dataseries X:
50	47
50	55
52	51
47	45
39	41
52	52
45	45
52	51
44	44
55	55
59	59
53	50
50	49
53	54
51	52
54	55
75	75
63	64
56	53
59	55
53	52
51	51
58	51
63	59
56	57
52	57
58	60
54	53
60	59
57	59
57	56
56	57
47	47
45	45
53	51
53	53
52	53
47	47
48	44
51	50
54	54
63	59
56	56
52	52
64	62
50	50
56	56
62	61
166	56
56	57
64	63
55	54
61	60
60	55
55	55
59	55
62	62
55	55
62	61
53	55
57	55
64	64
65	66
62	62
50	50
71	71
56	54
53	53
50	50
64	64
76	77
55	55
57	58
57	56
66	66
59	59
58	54
54	59
63	61
64	62
63	62
60	55
78	75
68	68
61	61
68	63
56	56
70	67
61	61
62	61
55	57
64	66
59	58
54	56
62	63
53	52
68	68
54	55




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168676&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168676&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168676&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 Server'AstonUniversity' @ aston.wessa.net







Wilcoxon Test
StatisticP-value
Wilcoxon Test5058.50.51845

\begin{tabular}{lllllllll}
\hline
Wilcoxon Test \tabularnewline
 & Statistic & P-value \tabularnewline
Wilcoxon Test & 5058.5 & 0.51845 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168676&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]5058.5[/C][C]0.51845[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168676&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168676&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 Test5058.50.51845







Standard Deviations
Variable 112.99008
Variable 26.78423

\begin{tabular}{lllllllll}
\hline
Standard Deviations \tabularnewline
Variable 1 & 12.99008 \tabularnewline
Variable 2 & 6.78423 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168676&T=2

[TABLE]
[ROW][C]Standard Deviations[/C][/ROW]
[ROW][C]Variable 1[/C][C]12.99008[/C][/ROW]
[ROW][C]Variable 2[/C][C]6.78423[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168676&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168676&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 112.99008
Variable 26.78423



Parameters (Session):
par1 = two.sided ; par2 = 1 ; par3 = 2 ;
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):
par8 <- 'TRUE'
par7 <- '0.95'
par6 <- '0.0'
par5 <- 'unpaired'
par4 <- 'Wilcoxon-Mann_Whitney'
par3 <- '2'
par2 <- '1'
par1 <- 'two.sided'
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')