FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 15 Dec 2014 16:35:45 +0000
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/Dec/15/t1418661399andfni0hs5355q7.htm/, Retrieved Thu, 16 May 2024 06:53:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268731, Retrieved Thu, 16 May 2024 06:53:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60

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] [Verband tussen in...] [2014-12-15 16:35:45] [8a5be748fffbe1272db475ee7e612f22] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26 NA
51 NA
57 NA
37 NA
67 NA
43 NA
52 NA
52 NA
43 NA
84 NA
67 NA
49 NA
70 NA
52 NA
58 NA
68 NA
NA 62
43 NA
56 NA
NA 56
74 NA
65 NA
63 NA
58 NA
57 NA
63 NA
53 NA
NA 57
NA 51
64 NA
53 NA
29 NA
54 NA
51 NA
58 NA
43 NA
51 NA
53 NA
54 NA
NA 56
61 NA
47 NA
39 NA
48 NA
50 NA
35 NA
NA 30
68 NA
49 NA
NA 61
67 NA
NA 47
NA 56
NA 50
43 NA
NA 67
62 NA
57 NA
NA 41
54 NA
NA 45
NA 48
61 NA
56 NA
41 NA
43 NA
53 NA
NA 44
66 NA
58 NA
46 NA
NA 37
51 NA
51 NA
NA 56
NA 66
45 NA
37 NA
59 NA
42 NA
NA 38
66 NA
NA 34
53 NA
NA 49
NA 55
NA 49
NA 59
NA 40
NA 58
NA 60
NA 63
NA 56
NA 54
NA 52
NA 34
NA 69
NA 32
NA 48
NA 67
NA 58
NA 57
NA 42
NA 64
NA 58
NA 66
NA 26
NA 61
NA 52
NA 51
NA 55
NA 50
NA 60
NA 56
NA 63
NA 61
52 NA
16 NA
46 NA
56 NA
NA 52
NA 55
50 NA
59 NA
60 NA
52 NA
44 NA
67 NA
52 NA
55 NA
37 NA
54 NA
NA 72
51 NA
48 NA
60 NA
50 NA
63 NA
33 NA
67 NA
46 NA
54 NA
59 NA
61 NA
NA 33
47 NA
69 NA
52 NA
55 NA
55 NA
41 NA
73 NA
51 NA
52 NA
50 NA
51 NA
60 NA
56 NA
56 NA
29 NA
NA 66
NA 66
73 NA
55 NA
NA 64
NA 40
NA 46
NA 58
43 NA
61 NA
NA 51
NA 50
NA 52
NA 54
NA 66
NA 61
NA 80
NA 51
NA 56
56 NA
56 NA
NA 53
47 NA
25 NA
NA 47
46 NA
NA 50
NA 39
51 NA
NA 58
NA 35
NA 58
NA 60
NA 62
NA 63
NA 53
NA 46
NA 67
NA 59
NA 64
NA 38
NA 50
48 NA
NA 48
NA 47
NA 66
47 NA
NA 63
58 NA
NA 44
51 NA
NA 43
55 NA
NA 38
NA 56
NA 45
NA 50
NA 54
57 NA
60 NA
NA 55
56 NA
49 NA
NA 37
43 NA
59 NA
NA 46
NA 51
58 NA
NA 64
53 NA
48 NA
51 NA
NA 47
59 NA
NA 62
62 NA
51 NA
64 NA
52 NA
NA 67
50 NA
54 NA
58 NA
NA 56
63 NA
31 NA
NA 65
71 NA
NA 50
NA 57
NA 47
54 NA
NA 47
NA 57
43 NA
41 NA
63 NA
63 NA
56 NA
51 NA
NA 50
NA 22
41 NA
NA 59
NA 56
66 NA
NA 53
NA 42
NA 52
NA 54
NA 44
NA 62
NA 53
NA 50
NA 36
NA 76
NA 66
NA 62
NA 59
NA 47
NA 55
NA 58
NA 60
44 NA
NA 57
NA 45
58 NA
51 NA
57 NA
30 NA
46 NA
51 NA
56 NA
58 NA
44 NA
14 NA
53 NA
42 NA
NA 49
44 NA
NA 62
30 NA
46 NA
NA 56
50 NA
54 NA
48 NA
55 NA
35 NA
55 NA
41 NA
59 NA
54 NA
66 NA
55 NA
45 NA
51 NA
47 NA
42 NA
53 NA
53 NA
41 NA
55 NA
55 NA
46 NA
63 NA
43 NA
65 NA
59 NA
39 NA
44 NA
NA 60
57 NA
NA 67
NA 52
NA 52
69 NA
46 NA
46 NA
NA 53
40 NA
70 NA
54 NA
77 NA
NA 45
60 NA
NA 47
50 NA
66 NA
60 NA
NA 41
NA 53
NA 34
51 NA
69 NA
60 NA
NA 45
58 NA
39 NA
51 NA
52 NA
49 NA
63 NA
NA 44
51 NA
52 NA
NA 60
NA 53
NA 53
52 NA
31 NA
NA 51
NA 65
NA 51
NA 49
61 NA
NA 58
NA 62
54 NA
NA 52
72 NA
NA 50
65 NA
NA 53
56 NA
63 NA
NA 62
NA 66
NA 50
45 NA
NA 58
52 NA
NA 53
68 NA
NA 59
NA 58
NA 52
45 NA
NA 58
70 NA
69 NA
NA 71
46 NA
NA 58
39 NA
NA 46
NA 64
NA 67
NA 44
54 NA
41 NA
68 NA
63 NA
57 NA
61 NA
39 NA
NA 69
NA 64
NA 38
59 NA
51 NA
NA 59
51 NA
65 NA
NA 47
50 NA
NA 57
21 NA
47 NA
NA 51
37 NA
NA 67
NA 43
58 NA
51 NA
40 NA
NA 41
NA 58
NA 64
64 NA
58 NA
NA 50
NA 59
NA 55
NA 59
NA 58
NA 41
56 NA
63 NA
NA 77
60 NA
NA 58
64 NA
47 NA
46 NA
NA 62
NA 60
50 NA
46 NA
44 NA
58 NA
NA 56
NA 43
NA 54
NA 54
NA 56
NA 65
NA 66
NA 62
58 NA
NA 67
25 NA
56 NA
NA 53
56 NA
59 NA
46 NA
NA 49
NA 56
NA 76
NA 33
49 NA
53 NA
58 NA
NA 72
NA 51
NA 42
NA 69
NA 51
54 NA
52 NA
59 NA
NA 51
NA 67
NA 64
NA 58
NA NA
NA NA
NA NA
NA NA
53 NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA

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=268731&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=268731&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268731&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 (unpaired)
Mean of Sample 152.6861313868613
Mean of Sample 254.09375
t-stat-1.54731221213145
df496
p-value0.122425759919747
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.19499565839134,0.379758432113963]
F-test to compare two variances
F-stat1.12828564739651
df273
p-value0.348190166540619
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.876619153770315,1.44754665684649]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 52.6861313868613 \tabularnewline
Mean of Sample 2 & 54.09375 \tabularnewline
t-stat & -1.54731221213145 \tabularnewline
df & 496 \tabularnewline
p-value & 0.122425759919747 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-3.19499565839134,0.379758432113963] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.12828564739651 \tabularnewline
df & 273 \tabularnewline
p-value & 0.348190166540619 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.876619153770315,1.44754665684649] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268731&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]52.6861313868613[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]54.09375[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.54731221213145[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]0.122425759919747[/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][-3.19499565839134,0.379758432113963][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.12828564739651[/C][/ROW]
[ROW][C]df[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]0.348190166540619[/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][0.876619153770315,1.44754665684649][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268731&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268731&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 (unpaired)
Mean of Sample 152.6861313868613
Mean of Sample 254.09375
t-stat-1.54731221213145
df496
p-value0.122425759919747
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.19499565839134,0.379758432113963]
F-test to compare two variances
F-stat1.12828564739651
df273
p-value0.348190166540619
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.876619153770315,1.44754665684649]






Welch Two Sample t-test (unpaired)
Mean of Sample 152.6861313868613
Mean of Sample 254.09375
t-stat-1.55672371469585
df486.210047046381
p-value0.120186740809848
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.18427719433091,0.369039968053533]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 52.6861313868613 \tabularnewline
Mean of Sample 2 & 54.09375 \tabularnewline
t-stat & -1.55672371469585 \tabularnewline
df & 486.210047046381 \tabularnewline
p-value & 0.120186740809848 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-3.18427719433091,0.369039968053533] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268731&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]52.6861313868613[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]54.09375[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.55672371469585[/C][/ROW]
[ROW][C]df[/C][C]486.210047046381[/C][/ROW]
[ROW][C]p-value[/C][C]0.120186740809848[/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][-3.18427719433091,0.369039968053533][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268731&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268731&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 (unpaired)
Mean of Sample 152.6861313868613
Mean of Sample 254.09375
t-stat-1.55672371469585
df486.210047046381
p-value0.120186740809848
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.18427719433091,0.369039968053533]






Wicoxon rank sum test with continuity correction (unpaired)
W28256.5
p-value0.127819990716562
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.084332638164755
p-value0.344701613279593
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0684632429614181
p-value0.610276642774124

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 28256.5 \tabularnewline
p-value & 0.127819990716562 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.084332638164755 \tabularnewline
p-value & 0.344701613279593 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0684632429614181 \tabularnewline
p-value & 0.610276642774124 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268731&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]28256.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.127819990716562[/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]0.084332638164755[/C][/ROW]
[ROW][C]p-value[/C][C]0.344701613279593[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0684632429614181[/C][/ROW]
[ROW][C]p-value[/C][C]0.610276642774124[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268731&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268731&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 (unpaired)
W28256.5
p-value0.127819990716562
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.084332638164755
p-value0.344701613279593
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0684632429614181
p-value0.610276642774124


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.0 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.0 ;
R code (references can be found in the software module):
par6 <- '0.0'
par5 <- 'unpaired'
par4 <- 'two.sided'
par3 <- '0.95'
par2 <- '2'
par1 <- '1'
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')