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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_twosampletests_mean.wasp
Title produced by softwarePaired and Unpaired Two Samples Tests about the Mean
Date of computationTue, 21 Oct 2014 08:47:40 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/21/t1413877695p7scknmf4ahzw4x.htm/, Retrieved Fri, 01 Nov 2024 00:00:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=244321, Retrieved Fri, 01 Nov 2024 00:00:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact469

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2010-11-01 13:07:12] [b98453cac15ba1066b407e146608df68]
- RMP     [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-21 07:47:40] [63a9f0ea7bb98050796b649e85481845] [Current]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-23 17:26:56] [32b17a345b130fdf5cc88718ed94a974]
- RMPD      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-10-28 15:12:26] [9dcc46711c3068bfcecf3b31ff5fbf47]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Q1] [2014-10-29 09:14:51] [eee95947b6243a1febfcd5f41483d733]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [WS 5 Question 1 T...] [2014-10-29 09:19:25] [be945163e51ed825733188af308451be]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Q1] [2014-10-29 09:22:53] [eee95947b6243a1febfcd5f41483d733]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 09:38:05] [2b9d0c54c8c845c625e475ed5f1f3af1]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 10:04:32] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:43:43] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:44:41] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:46:01] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:47:07] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:48:02] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:48:47] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Notched Boxplots] [] [2014-12-12 09:49:39] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Histogram] [] [2014-12-12 09:59:31] [eee95947b6243a1febfcd5f41483d733]
- RMPD        [Histogram] [] [2014-12-12 10:02:19] [eee95947b6243a1febfcd5f41483d733]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 10:53:05] [b2fe7fef0850359c2a41ad606a8f04c2]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 11:36:30] [fa1b8827d7de91b8b87087311d3d9fa1]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 11:37:46] [394a9522c47495260fca596e959e6202]
-           [Paired and Unpaired Two Samples Tests about the Mean] [WS5 - task1] [2014-10-29 12:29:38] [81f624c2f0b20a2549c93e7c3dccf981]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 12:40:12] [e493208d2907342b139e6792bbaea494]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [Task 1 WS5] [2014-10-29 12:42:07] [805021881bfa5340347077d26b077617]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [Task1 WS5] [2014-10-29 12:49:23] [805021881bfa5340347077d26b077617]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 12:51:05] [eee95947b6243a1febfcd5f41483d733]
-           [Paired and Unpaired Two Samples Tests about the Mean] [e] [2014-10-29 13:02:00] [861cf3a5e9222e55170c5866e1781f14]
- R P       [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:06:01] [044144d0728beecdb08e0d94daaff202]
-           [Paired and Unpaired Two Samples Tests about the Mean] [t-test E] [2014-10-29 13:09:22] [861cf3a5e9222e55170c5866e1781f14]
-    D        [Paired and Unpaired Two Samples Tests about the Mean] [t-test T] [2014-10-29 13:20:56] [861cf3a5e9222e55170c5866e1781f14]
-    D          [Paired and Unpaired Two Samples Tests about the Mean] [t-test S] [2014-10-29 13:26:07] [861cf3a5e9222e55170c5866e1781f14]
-    D            [Paired and Unpaired Two Samples Tests about the Mean] [t-test E3] [2014-10-29 13:37:57] [861cf3a5e9222e55170c5866e1781f14]
-    D              [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:42:18] [861cf3a5e9222e55170c5866e1781f14]
-    D                [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:48:57] [861cf3a5e9222e55170c5866e1781f14]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:10:27] [765bd0d5d4a0c852014c120c6930661d]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:14:49] [eee95947b6243a1febfcd5f41483d733]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:15:47] [7b576ab45e161dc8fb6fe50455a3800c]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [Task2 WS5] [2014-10-29 13:16:20] [805021881bfa5340347077d26b077617]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:20:24] [d69b52d23ca73e15a0c741afa583703c]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [Task3 WS5] [2014-10-29 13:22:07] [805021881bfa5340347077d26b077617]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [WS 5 Task 1] [2014-10-29 13:26:05] [fa1b8827d7de91b8b87087311d3d9fa1]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:35:13] [d253a55552bf9917a397def3be261e30]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:36:02] [ae96d02647dd9ad9c105f1fa6642e295]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:36:31] [ae96d02647dd9ad9c105f1fa6642e295]
-           [Paired and Unpaired Two Samples Tests about the Mean] [WS5-1] [2014-10-29 13:41:57] [40df8d8b5657a9599acc6ccced535535]
-           [Paired and Unpaired Two Samples Tests about the Mean] [question 1] [2014-10-29 13:43:50] [2ba32e9656c7c3fdddad3ba3f1588288]
- R PD      [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:44:09] [c2c160edf30e228bd3a949bf24376c2c]
- R         [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:45:23] [3cc57788b191749bdc089f5fad42e0f8]
- R P       [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:51:19] [c2c160edf30e228bd3a949bf24376c2c]
-    D      [Paired and Unpaired Two Samples Tests about the Mean] [workshop 5 bereke...] [2014-10-29 13:58:28] [b007041690f75f30ec26eb43925b7b35]

[Truncated]
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Dataset

Dataseries X:
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Histogram
Boxplots 
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244321&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244321&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244321&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.363636363636364
t-stat-3.80664761144709
df32
p-value0.000600974473770437
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.558217819444907,-0.16905490782782]
F-test to compare two variances
F-stat1.3
df32
p-value0.462180712842677
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.642054974596472,2.63217336032971]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -0.363636363636364 \tabularnewline
t-stat & -3.80664761144709 \tabularnewline
df & 32 \tabularnewline
p-value & 0.000600974473770437 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.558217819444907,-0.16905490782782] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.3 \tabularnewline
df & 32 \tabularnewline
p-value & 0.462180712842677 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.642054974596472,2.63217336032971] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244321&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-0.363636363636364[/C][/ROW]
[ROW][C]t-stat[/C][C]-3.80664761144709[/C][/ROW]
[ROW][C]df[/C][C]32[/C][/ROW]
[ROW][C]p-value[/C][C]0.000600974473770437[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][-0.558217819444907,-0.16905490782782][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.3[/C][/ROW]
[ROW][C]df[/C][C]32[/C][/ROW]
[ROW][C]p-value[/C][C]0.462180712842677[/C][/ROW]
[ROW][C]H0 value[/C][C]1[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][0.642054974596472,2.63217336032971][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244321&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244321&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:

Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.363636363636364
t-stat-3.80664761144709
df32
p-value0.000600974473770437
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.558217819444907,-0.16905490782782]
F-test to compare two variances
F-stat1.3
df32
p-value0.462180712842677
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.642054974596472,2.63217336032971]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.363636363636364
t-stat-3.80664761144709
df32
p-value0.000600974473770437
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.558217819444907,-0.16905490782782]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -0.363636363636364 \tabularnewline
t-stat & -3.80664761144709 \tabularnewline
df & 32 \tabularnewline
p-value & 0.000600974473770437 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.558217819444907,-0.16905490782782] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244321&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-0.363636363636364[/C][/ROW]
[ROW][C]t-stat[/C][C]-3.80664761144709[/C][/ROW]
[ROW][C]df[/C][C]32[/C][/ROW]
[ROW][C]p-value[/C][C]0.000600974473770437[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][-0.558217819444907,-0.16905490782782][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244321&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244321&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:

Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.363636363636364
t-stat-3.80664761144709
df32
p-value0.000600974473770437
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.558217819444907,-0.16905490782782]






Wicoxon rank sum test with continuity correction (paired)
W7.5
p-value0.00151653831170848
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.363636363636364
p-value0.025463957781115
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.393939393939394
p-value0.0119375646999563

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 7.5 \tabularnewline
p-value & 0.00151653831170848 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.363636363636364 \tabularnewline
p-value & 0.025463957781115 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.393939393939394 \tabularnewline
p-value & 0.0119375646999563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244321&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]7.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.00151653831170848[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributions of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.363636363636364[/C][/ROW]
[ROW][C]p-value[/C][C]0.025463957781115[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.393939393939394[/C][/ROW]
[ROW][C]p-value[/C][C]0.0119375646999563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244321&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244321&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Wicoxon rank sum test with continuity correction (paired)
W7.5
p-value0.00151653831170848
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.363636363636364
p-value0.025463957781115
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.393939393939394
p-value0.0119375646999563


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) #column number of first sample
par2 <- as.numeric(par2) #column number of second sample
par3 <- as.numeric(par3) #confidence (= 1 - alpha)
if (par5 == 'unpaired') paired <- FALSE else paired <- TRUE
par6 <- as.numeric(par6) #H0
z <- t(y)
if (par1 == par2) stop('Please, select two different column numbers')
if (par1 < 1) stop('Please, select a column number greater than zero for the first sample')
if (par2 < 1) stop('Please, select a column number greater than zero for the second sample')
if (par1 > length(z[1,])) stop('The column number for the first sample should be smaller')
if (par2 > length(z[1,])) stop('The column number for the second sample should be smaller')
if (par3 <= 0) stop('The confidence level should be larger than zero')
if (par3 >= 1) stop('The confidence level should be smaller than zero')
(r.t <- t.test(z[,par1],z[,par2],var.equal=TRUE,alternative=par4,paired=paired,mu=par6,conf.level=par3))
(v.t <- var.test(z[,par1],z[,par2],conf.level=par3))
(r.w <- t.test(z[,par1],z[,par2],var.equal=FALSE,alternative=par4,paired=paired,mu=par6,conf.level=par3))
(w.t <- wilcox.test(z[,par1],z[,par2],alternative=par4,paired=paired,mu=par6,conf.level=par3))
(ks.t <- ks.test(z[,par1],z[,par2],alternative=par4))
m1 <- mean(z[,par1],na.rm=T)
m2 <- mean(z[,par2],na.rm=T)
mdiff <- m1 - m2
newsam1 <- z[!is.na(z[,par1]),par1]
newsam2 <- z[,par2]+mdiff
newsam2 <- newsam2[!is.na(newsam2)]
(ks1.t <- ks.test(newsam1,newsam2,alternative=par4))
mydf <- data.frame(cbind(z[,par1],z[,par2]))
colnames(mydf) <- c('Variable 1','Variable 2')
bitmap(file='test1.png')
boxplot(mydf, notch=TRUE, ylab='value',main=main)
dev.off()
bitmap(file='test2.png')
qqnorm(z[,par1],main='Normal QQplot - Variable 1')
qqline(z[,par1])
dev.off()
bitmap(file='test3.png')
qqnorm(z[,par2],main='Normal QQplot - Variable 2')
qqline(z[,par2])
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Two Sample t-test (',par5,')',sep=''),2,TRUE)
a<-table.row.end(a)
if(!paired){
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 1',header=TRUE)
a<-table.element(a,r.t$estimate[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 2',header=TRUE)
a<-table.element(a,r.t$estimate[[2]])
a<-table.row.end(a)
} else {
a<-table.row.start(a)
a<-table.element(a,'Difference: Mean1 - Mean2',header=TRUE)
a<-table.element(a,r.t$estimate)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'t-stat',header=TRUE)
a<-table.element(a,r.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'df',header=TRUE)
a<-table.element(a,r.t$parameter[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,r.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,r.t$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,r.t$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI Level',header=TRUE)
a<-table.element(a,attr(r.t$conf.int,'conf.level'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI',header=TRUE)
a<-table.element(a,paste('[',r.t$conf.int[1],',',r.t$conf.int[2],']',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'F-test to compare two variances',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'F-stat',header=TRUE)
a<-table.element(a,v.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'df',header=TRUE)
a<-table.element(a,v.t$parameter[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,v.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,v.t$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,v.t$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI Level',header=TRUE)
a<-table.element(a,attr(v.t$conf.int,'conf.level'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI',header=TRUE)
a<-table.element(a,paste('[',v.t$conf.int[1],',',v.t$conf.int[2],']',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Welch Two Sample t-test (',par5,')',sep=''),2,TRUE)
a<-table.row.end(a)
if(!paired){
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 1',header=TRUE)
a<-table.element(a,r.w$estimate[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 2',header=TRUE)
a<-table.element(a,r.w$estimate[[2]])
a<-table.row.end(a)
} else {
a<-table.row.start(a)
a<-table.element(a,'Difference: Mean1 - Mean2',header=TRUE)
a<-table.element(a,r.w$estimate)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'t-stat',header=TRUE)
a<-table.element(a,r.w$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'df',header=TRUE)
a<-table.element(a,r.w$parameter[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,r.w$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,r.w$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,r.w$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI Level',header=TRUE)
a<-table.element(a,attr(r.w$conf.int,'conf.level'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI',header=TRUE)
a<-table.element(a,paste('[',r.w$conf.int[1],',',r.w$conf.int[2],']',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Wicoxon rank sum test with continuity correction (',par5,')',sep=''),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'W',header=TRUE)
a<-table.element(a,w.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,w.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,w.t$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,w.t$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Kolmogorov-Smirnov Test to compare Distributions of two Samples',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'KS Statistic',header=TRUE)
a<-table.element(a,ks.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,ks.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'KS Statistic',header=TRUE)
a<-table.element(a,ks1.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,ks1.t$p.value)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')