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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 19:16:02 +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/t1418670985i3959i2atp79nrk.htm/, Retrieved Thu, 31 Oct 2024 23:32:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268934, Retrieved Thu, 31 Oct 2024 23:32:38 +0000
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Original text written by user:
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User-defined keywords
Estimated Impact94
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] [] [2014-12-12 12:46:54] [7b949ef3605c038fc6e10efeab34f433]
- R P     [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-15 19:16:02] [2b74e5be20a95dee0bfccc444f4c1798] [Current]
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Dataseries X:
26	50
51	68
57	62
37	54
67	71
43	54
52	65
52	73
43	52
84	84
67	42
49	66
70	65
52	78
58	73
68	75
62	72
43	66
56	70
56	61
74	81
65	71
63	69
58	71
57	72
63	68
53	70
57	68
51	61
64	67
53	76
29	70
54	60
51	77
58	72
43	69
51	71
53	62
54	70
56	64
61	58
47	76
39	52
48	59
50	68
35	76
30	65
68	67
49	59
61	69
67	76
47	63
56	75
50	63
43	60
67	73
62	63
57	70
41	75
54	66
45	63
48	63
61	64
56	70
41	75
43	61
53	60
44	62
66	73
58	61
46	66
37	64
51	59
51	64
56	60
66	56
45	66
37	78
59	53
42	67
38	59
66	66
34	68
53	71
49	66
55	73
49	72
59	71
40	59
58	64
60	66
63	78
56	68
54	73
52	62
34	65
69	68
32	65
48	60
67	71
58	65
57	68
42	64
64	74
58	69
66	76
26	68
61	72
52	67
51	63
55	59
50	73
60	66
56	62
63	69
61	66
52	51
16	56
46	67
56	69
52	57
55	56
50	55
59	63
60	67
52	65
44	47
67	76
52	64
55	68
37	64
54	65
72	71
51	63
48	60
60	68
50	72
63	70
33	61
67	61
46	62
54	71
59	71
61	51
33	56
47	70
69	73
52	76
55	59
55	68
41	48
73	52
51	59
52	60
50	59
51	57
60	79
56	60
56	60
29	59
66	62
66	59
73	61
55	71
64	57
40	66
46	63
58	69
43	58
61	59
51	48
50	66
52	73
54	67
66	61
61	68
80	75
51	62
56	69
56	58
56	60
53	74
47	55
25	62
47	63
46	69
50	58
39	58
51	68
58	72
35	62
58	62
60	65
62	69
63	66
53	72
46	62
67	75
59	58
64	66
38	55
50	47
48	72
48	62
47	64
66	64
47	19
63	50
58	68
44	70
51	79
43	69
55	71
38	48
56	66
45	73
50	74
54	66
57	71
60	74
55	78
56	75
49	53
37	60
43	50
59	70
46	69
51	65
58	78
64	78
53	59
48	72
51	70
47	63
59	63
62	71
62	74
51	67
64	66
52	62
67	80
50	73
54	67
58	61
56	73
63	74
31	32
65	69
71	69
50	84
57	64
47	58
54	60
47	59
57	78
43	57
41	60
63	68
63	68
56	73
51	69
50	67
22	60
41	65
59	66
56	74
66	81
53	72
42	55
52	49
54	74
44	53
62	64
53	65
50	57
36	51
76	80
66	67
62	70
59	74
47	75
55	70
58	69
60	65
44	55
57	71
45	65
58	69
51	48
57	69
30	68
46	74
51	67
56	65
58	63
44	74
14	39
53	68
42	69
49	68
44	63
62	67
30	70
46	68
56	66
50	70
54	78
48	59
55	62
35	75
55	74
41	73
59	62
54	69
66	65
55	67
45	73
51	52
47	61
42	53
53	63
53	78
41	65
55	77
55	69
46	68
63	76
43	63
65	41
59	76
39	67
44	69
60	59
57	73
67	72
52	52
52	65
69	63
46	78
46	56
53	68
40	56
70	64
54	68
77	75
45	67
60	55
47	73
50	66
66	75
60	77
41	65
53	75
34	57
51	61
69	71
60	72
45	62
58	66
39	66
51	63
52	60
49	64
63	74
44	59
51	71
52	69
60	63
53	73
53	55
52	77
31	70
51	64
65	78
51	60
49	66
61	77
58	68
62	78
54	68
52	60
72	65
50	64
65	69
53	72
56	50
63	72
62	71
66	80
50	74
45	64
58	69
52	76
53	75
68	79
59	73
58	60
52	76
45	55
58	53
70	62
69	69
71	78
46	68
58	67
39	75
46	59
64	73
67	70
44	59
54	64
41	63
68	67
63	58
57	71
61	79
39	53
69	76
64	66
38	64
59	57
51	67
59	72
51	58
65	74
47	57
50	62
57	74
21	54
47	62
51	66
37	64
67	74
43	71
58	66
51	66
40	63
41	65
58	70
64	66
64	66
58	78
50	77
59	72
55	65
59	67
58	72
41	58
56	84
63	67
77	84
60	58
58	63
64	75
47	55
46	72
62	58
60	69
50	54
46	58
44	67
58	77
56	80
43	67
54	75
54	71
56	72
65	75
66	79
62	76
58	72
67	81
25	52
56	76
53	60
56	72
59	77
46	64
49	67
56	72
76	79
33	40
49	71
53	73
58	75
72	70
51	66
42	66
69	73
51	74
54	58
52	51
59	75
51	70
67	50
64	64
58	77




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=268934&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=268934&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268934&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.8752515090543
t-stat-27.4310093026027
df496
p-value1.7453256518866e-101
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.7974471443704,-11.9530558737383]
F-test to compare two variances
F-stat1.53707146967254
df496
p-value1.87643862048503e-06
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.28874197565396,1.83325192126408]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -12.8752515090543 \tabularnewline
t-stat & -27.4310093026027 \tabularnewline
df & 496 \tabularnewline
p-value & 1.7453256518866e-101 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-13.7974471443704,-11.9530558737383] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.53707146967254 \tabularnewline
df & 496 \tabularnewline
p-value & 1.87643862048503e-06 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.28874197565396,1.83325192126408] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268934&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-12.8752515090543[/C][/ROW]
[ROW][C]t-stat[/C][C]-27.4310093026027[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]1.7453256518866e-101[/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][-13.7974471443704,-11.9530558737383][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.53707146967254[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]1.87643862048503e-06[/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][1.28874197565396,1.83325192126408][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268934&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268934&T=1

As an alternative you can also use a QR Code:  

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

Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.8752515090543
t-stat-27.4310093026027
df496
p-value1.7453256518866e-101
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.7974471443704,-11.9530558737383]
F-test to compare two variances
F-stat1.53707146967254
df496
p-value1.87643862048503e-06
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.28874197565396,1.83325192126408]







Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.8752515090543
t-stat-27.4310093026027
df496
p-value1.7453256518866e-101
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.7974471443704,-11.9530558737383]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -12.8752515090543 \tabularnewline
t-stat & -27.4310093026027 \tabularnewline
df & 496 \tabularnewline
p-value & 1.7453256518866e-101 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-13.7974471443704,-11.9530558737383] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268934&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-12.8752515090543[/C][/ROW]
[ROW][C]t-stat[/C][C]-27.4310093026027[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]1.7453256518866e-101[/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][-13.7974471443704,-11.9530558737383][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268934&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268934&T=2

As an alternative you can also use a QR Code:  

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

Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.8752515090543
t-stat-27.4310093026027
df496
p-value1.7453256518866e-101
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.7974471443704,-11.9530558737383]







Wicoxon rank sum test with continuity correction (paired)
W4834.5
p-value5.02293265273719e-70
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.557344064386318
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0784708249496982
p-value0.0937317812498593

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 4834.5 \tabularnewline
p-value & 5.02293265273719e-70 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.557344064386318 \tabularnewline
p-value & 0 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0784708249496982 \tabularnewline
p-value & 0.0937317812498593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268934&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]4834.5[/C][/ROW]
[ROW][C]p-value[/C][C]5.02293265273719e-70[/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]0.557344064386318[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0784708249496982[/C][/ROW]
[ROW][C]p-value[/C][C]0.0937317812498593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268934&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268934&T=3

As an alternative you can also use a QR Code:  

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

Wicoxon rank sum test with continuity correction (paired)
W4834.5
p-value5.02293265273719e-70
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.557344064386318
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0784708249496982
p-value0.0937317812498593



Parameters (Session):
par1 = 7 ; par2 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0.0 ;
R code (references can be found in the software module):
par6 <- '0.0'
par5 <- 'paired'
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('Totale intrinsieke motivatie','Totale extrinsieke motivatie')
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')