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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 09:01:08 +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/t1413878507yym9jpotgx92f47.htm/, Retrieved Mon, 13 May 2024 00:10:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=244332, Retrieved Mon, 13 May 2024 00:10:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact245

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 13:31:55] [b98453cac15ba1066b407e146608df68]
- RMP     [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-21 08:01:08] [63a9f0ea7bb98050796b649e85481845] [Current]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Q5] [2014-10-29 09:41:42] [eee95947b6243a1febfcd5f41483d733]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 10:16:53] [2b9d0c54c8c845c625e475ed5f1f3af1]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 10:38:25] [eee95947b6243a1febfcd5f41483d733]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Ws 5 Question 5 p...] [2014-10-29 11:36:31] [be945163e51ed825733188af308451be]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 12:20:24] [fa1b8827d7de91b8b87087311d3d9fa1]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 12:25:41] [394a9522c47495260fca596e959e6202]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 12:27:35] [b2fe7fef0850359c2a41ad606a8f04c2]
-           [Paired and Unpaired Two Samples Tests about the Mean] [WS5 - task 5 - E] [2014-10-29 13:28:02] [81f624c2f0b20a2549c93e7c3dccf981]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:28:30] [7b576ab45e161dc8fb6fe50455a3800c]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q5.2] [2014-10-29 13:33:36] [ce9f16fa58bb2303d66047ab4343b505]
-           [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q5.2] [2014-10-29 13:34:42] [ce9f16fa58bb2303d66047ab4343b505]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:42:53] [e493208d2907342b139e6792bbaea494]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:51:09] [765bd0d5d4a0c852014c120c6930661d]
-             [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:51:29] [765bd0d5d4a0c852014c120c6930661d]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:52:27] [eee95947b6243a1febfcd5f41483d733]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 13:56:15] [ae96d02647dd9ad9c105f1fa6642e295]
-           [Paired and Unpaired Two Samples Tests about the Mean] [WS5-4] [2014-10-29 13:58:41] [40df8d8b5657a9599acc6ccced535535]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 14:09:09] [d253a55552bf9917a397def3be261e30]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 14:17:52] [bca3c6529212edfac3e771806c79a908]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 14:20:28] [6795cd14e59cd8fafcdf800c40b889d9]
-           [Paired and Unpaired Two Samples Tests about the Mean] [question 5] [2014-10-29 14:21:57] [2ba32e9656c7c3fdddad3ba3f1588288]
-   P       [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 14:29:47] [c2c160edf30e228bd3a949bf24376c2c]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 14:42:56] [3cc57788b191749bdc089f5fad42e0f8]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [WS 5 Task 5 E] [2014-10-29 14:49:30] [fa1b8827d7de91b8b87087311d3d9fa1]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 15:35:53] [fda96889f4ef6d31c0c28fd64d281011]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 15:39:47] [d69b52d23ca73e15a0c741afa583703c]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 15:40:46] [02fb6cbf799bcf1e525e4e01c2f27ada]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 15:55:07] [69bf0eb8b9b38defaaf4848d8c317571]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 17:29:33] [8d160a85bfd9526a7d0e42afc5fb569b]
-           [Paired and Unpaired Two Samples Tests about the Mean] [Q53] [2014-10-29 17:29:43] [9378e2688aa9dcfd1390615d31e9d404]
-           [Paired and Unpaired Two Samples Tests about the Mean] [Question 5 - E tr...] [2014-10-29 17:40:30] [1e921ed6280e31020168fe5cd3fc7265]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Question 5c] [2014-10-29 18:19:14] [c91e4c88cfd8ec1fc4fb1878ec426fb8]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Compendium 5] [2014-10-29 18:29:21] [006b54b8ce76f482b86cd20c6480b526]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-29 19:25:15] [93cb0d178904cf975da218b7c929e42d]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 08:22:47] [1a6d42b46b3d01bc960fcfb45e99fecd]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [ws 5 (8)] [2014-10-30 09:11:42] [55a850ac261e4a7d4f206113c00d6f60]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 11:01:50] [9922f47a08b670aeeb7c38448acbfea1]
-           [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 11:41:55] [4c4ebb0b36a379d1d949ba77427e658a]
-           [Paired and Unpaired Two Samples Tests about the Mean] [w] [2014-10-30 15:30:25] [118a39334d200089014f927b57d44a19]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 16:17:07] [78252ca1523d3477f114bddbfa59edb4]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 16:17:44] [78252ca1523d3477f114bddbfa59edb4]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 16:32:02] [69bf0eb8b9b38defaaf4848d8c317571]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 17:24:56] [261f60062b6e70d0e3f72a6ad4f04654]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [Q5] [2014-10-30 18:21:42] [1651e47f7f65f3a10bbbb444d4b26be7]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [ws5] [2014-10-30 19:11:13] [8523551e1e4e3cbe97fa25692e177b2e]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-30 19:16:44] [f12bfb29749f0c3f544bf278d0782c85]
-  M        [Paired and Unpaired Two Samples Tests about the Mean] [azeazeazeeaz] [2014-10-30 19:21:39] [2a42404c3b0fbfc7622e3301a77a3a9b]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [Question 5 E] [2014-10-30 19:23:04] [8f0f7d8870e334acea674e48ede2c797]

[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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244332&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244332&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244332&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'Gertrude Mary Cox' @ cox.wessa.net






Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.3
t-stat-2.75716190086342
df29
p-value0.00998129981286201
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.522536403265861,-0.077463596734139]
F-test to compare two variances
F-stat1.21707128099174
df32
p-value0.596030021488084
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.586134549517359,2.4945389374076]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -0.3 \tabularnewline
t-stat & -2.75716190086342 \tabularnewline
df & 29 \tabularnewline
p-value & 0.00998129981286201 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.522536403265861,-0.077463596734139] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.21707128099174 \tabularnewline
df & 32 \tabularnewline
p-value & 0.596030021488084 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.586134549517359,2.4945389374076] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244332&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-0.3[/C][/ROW]
[ROW][C]t-stat[/C][C]-2.75716190086342[/C][/ROW]
[ROW][C]df[/C][C]29[/C][/ROW]
[ROW][C]p-value[/C][C]0.00998129981286201[/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][-0.522536403265861,-0.077463596734139][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.21707128099174[/C][/ROW]
[ROW][C]df[/C][C]32[/C][/ROW]
[ROW][C]p-value[/C][C]0.596030021488084[/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][0.586134549517359,2.4945389374076][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244332&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244332&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 - Mean2-0.3
t-stat-2.75716190086342
df29
p-value0.00998129981286201
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.522536403265861,-0.077463596734139]
F-test to compare two variances
F-stat1.21707128099174
df32
p-value0.596030021488084
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.586134549517359,2.4945389374076]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.3
t-stat-2.75716190086342
df29
p-value0.00998129981286201
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.522536403265861,-0.077463596734139]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -0.3 \tabularnewline
t-stat & -2.75716190086342 \tabularnewline
df & 29 \tabularnewline
p-value & 0.00998129981286201 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.522536403265861,-0.077463596734139] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244332&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-0.3[/C][/ROW]
[ROW][C]t-stat[/C][C]-2.75716190086342[/C][/ROW]
[ROW][C]df[/C][C]29[/C][/ROW]
[ROW][C]p-value[/C][C]0.00998129981286201[/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][-0.522536403265861,-0.077463596734139][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244332&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244332&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 - Mean2-0.3
t-stat-2.75716190086342
df29
p-value0.00998129981286201
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.522536403265861,-0.077463596734139]






Wicoxon rank sum test with continuity correction (paired)
W14
p-value0.0140286306942676
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.339393939393939
p-value0.0535535045537597
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.393939393939394
p-value0.0152344169341024

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 14 \tabularnewline
p-value & 0.0140286306942676 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.339393939393939 \tabularnewline
p-value & 0.0535535045537597 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.393939393939394 \tabularnewline
p-value & 0.0152344169341024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=244332&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]14[/C][/ROW]
[ROW][C]p-value[/C][C]0.0140286306942676[/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]0.339393939393939[/C][/ROW]
[ROW][C]p-value[/C][C]0.0535535045537597[/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]0.0152344169341024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=244332&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=244332&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)
W14
p-value0.0140286306942676
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.339393939393939
p-value0.0535535045537597
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.393939393939394
p-value0.0152344169341024


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')