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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 06:03:11 -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/t1338545011jf87tiiqf4qqgdp.htm/, Retrieved Thu, 02 May 2024 04:42:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168535, Retrieved Thu, 02 May 2024 04:42:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
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]
- RMPD    [CARE Data - Boxplots and Scatterplot Matrix] [Female weight aga...] [2012-06-01 09:15:24] [553711af6a3a99aac240956ee7ba8417]
- RMPD        [T-Tests] [Repeated t test f...] [2012-06-01 10:03:11] [50ef738b441df67da458e2632ba394c1] [Current]
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Dataseries X:
77	77
68	70
76	76
76	77
69	73
71	71
65	64
70	75
92	101
76	75
119	124
65	66
66	70
101	100
75	73
79	76
64	65
69	69
88	86
65	67
80	80
78	80
85	82
73	71.3409
82	85
74	73
102	107
64	71.3409
65	64
73	74
75	70
57	58
68	69
71	71
71	76
97	98
80	76
66	66
69	70
69	70
55	56
59	61
62	66
70	68
84	86
69	71
88	87
103	101
63	63
84	90
79	79
67	67
83	83
96	94
75	76
65	66
78	77
69	73
67	71.3409
87	89
83	84
90	91
85	83
66	68
88	86
54	58
69	68
56	58
96	95
76	75
61	61
82	71.3409
62	64
71	68
66	67
81	82
68	68
80	78
82	71.3409
70	70
76	75
88	93
89	86
74	71
83	80
81	71.3409
90	91
79	81




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168535&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168535&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168535&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'Gwilym Jenkins' @ jenkins.wessa.net







Wilcoxon Test
StatisticP-value
Wilcoxon Test1155.50.20824

\begin{tabular}{lllllllll}
\hline
Wilcoxon Test \tabularnewline
 & Statistic & P-value \tabularnewline
Wilcoxon Test & 1155.5 & 0.20824 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168535&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]1155.5[/C][C]0.20824[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168535&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168535&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 Test1155.50.20824







Standard Deviations
Variable 111.89034
Variable 211.92917

\begin{tabular}{lllllllll}
\hline
Standard Deviations \tabularnewline
Variable 1 & 11.89034 \tabularnewline
Variable 2 & 11.92917 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168535&T=2

[TABLE]
[ROW][C]Standard Deviations[/C][/ROW]
[ROW][C]Variable 1[/C][C]11.89034[/C][/ROW]
[ROW][C]Variable 2[/C][C]11.92917[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168535&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168535&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 111.89034
Variable 211.92917



Parameters (Session):
par1 = 10 ;
Parameters (R input):
par1 = two.sided ; par2 = 1 ; par3 = 2 ; par4 = Wilcoxon-Mann_Whitney ; par5 = paired ; 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], 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')