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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 computationSat, 27 Oct 2012 07:02:31 -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/Oct/27/t1351335766ft2bnvl67egek9k.htm/, Retrieved Thu, 02 May 2024 23:57:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=184167, Retrieved Thu, 02 May 2024 23:57:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Aston University Statistical Software] [Morning Sickness ...] [2009-11-16 16:26:06] [74be16979710d4c4e7c6647856088456]
- R     [Aston University Statistical Software] [Morning Sickness ...] [2009-11-16 17:22:16] [74be16979710d4c4e7c6647856088456]
-   P     [T-Tests] [Morning Sickness ...] [2010-11-09 11:12:43] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM        [T-Tests] [Morning Sickness ...] [2011-11-07 09:34:35] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R  D          [T-Tests] [pilots] [2012-10-27 11:02:31] [9751fdb70e008746130355e091b7273f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
Standard	New-Method
41.81	46.12
40.25	50.9
50.37	47.32
43.12	47.05
40.46	49.55
42.89	48.33
54.29	44.49
56.13	51.64
51.76	46.55
42.92	54.79
45.58	47.51
47.37	50.83
48.27	48.41
47.02	53.83
52.23	52.95
64.02	56.88
52.36	48.5
53.97	53.29
60.45	54.06
47.76	56.66
47.44	48.88
48.35	44.46
49.21	49.63
52.12	49.12
44.39	56.88
48.89	46.89
54.04	55.97
40.31	50.42
50.51	52.67
52.33	51.28
44.52	55.89
55.59	54.55
54.27	48.8
49.18	52.39
40.75	56.8
45.36	46.69
43.54	44.01
48.82	50.51
54.05	56.01
57.47	61.45

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Engine error message
Error in as.vector(data) : object 'Standard' not found
Calls: array -> as.vector
Execution halted


\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Engine error message & 
Error in as.vector(data) : object 'Standard' not found
Calls: array -> as.vector
Execution halted

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184167&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in as.vector(data) : object 'Standard' not found
Calls: array -> as.vector
Execution halted

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184167&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Engine error message
Error in as.vector(data) : object 'Standard' not found
Calls: array -> as.vector
Execution halted


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = two.sided ; par2 = 1 ; par3 = 2 ; par4 = T-Test ; par5 = unpaired ; par6 = 0.0 ; par7 = 0.95 ; par8 = TRUE ;
Parameters (R input):
par1 = two.sided ; par2 = 1 ; par3 = 2 ; par4 = T-Test ; 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')