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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 computationTue, 17 Dec 2013 05:38:53 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/17/t13872767635vrvrjzvrqtq31n.htm/, Retrieved Fri, 29 Mar 2024 08:12:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232405, Retrieved Fri, 29 Mar 2024 08:12:58 +0000
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-       [Paired and Unpaired Two Samples Tests about the Mean] [] [2013-12-17 10:38:53] [9e6a405f514733ea23d87e4507d39d29] [Current]
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Dataseries X:
22	0
2	1
0	0
4	0
14	5
2	0
0	4
4	4
6	0
25	0
0	0
25	5
0	0
2	2
30	3
1	0
0	0
0	0
8	0
0	4
0	0
0	8
6	0
0	0
6	0
12	3
1	0
20	24
5	15
0	0
21	12
3	0
5	0
8	0
10	4
5	1
8	0
6	16
15	9
9	0
14	8
9	10
5	0
9	6
10	0
12	0
9	15
7	0
15	0
14	0
16	0
6	0
6	0
2	0
8	10
0	7
6	2
4	0
15	2
0	0
12	3
0	12
13	0
18	3
4	0
9	0
12	0
14	8
0	0
4	7
12	0
15	18
0	0
30	13
0	0
0	0
3	0
2	0
15	0
3	2
4	0
12	9
8	16
12	10
18	0
15	7
3	8
0	0
0	0
21	0
10	0
5	1
0	0
1	0
0	0
6	0
12	0
10	20
0	9
25	0
3	0
15	0
10	0
15	4
4	0
10	2
2	0
12	0
9	0
1	28
4	0
2	0
0	0
1	0
0	0
0	0
0	0
18	10
3	0
6	0
0	16
2	1
4	10
15	0
6	0
30	15
3	10
18	0
10	0
0	0
7	2
0	3
22	4
7	1
4	4
15	0
5	0
14	8
11	0
24	0
24	6
0	0
20	2
12	0
7	0
0	0
28	0
12	0
15	27
0	0
7	4
8	0
30	0
14	0
3	0
3	1
0	0
15	4
0	0
11	0
1	0
30	9
4	0
0	0
3	0
0	0
0	17
0	3
0	0
12	0
26	0
0	0
6	12
0	5
4	17
19	0
16	0
8	0
10	2
6	0
2	0
0	4
30	2
8	1
0	0
10	18
15	0
21	0
1	3
5	9
0	2
4	12
1	0
4	0
24	4
11	0
0	0
0	0
0	0
1	0
0	0
30	0
6	0
0	0
9	21
5	3
2	0
8	0
16	0
0	20
12	0
0	0
0	18
9	0
10	1
5	0
2	0
6	5
0	0
0	0
0	3
24	0
0	0
18	11
1	0
4	0
0	0
2	2
12	15
0	4
10	0
0	0
0	0
0	0
2	0
0	1
20	0
0	0
8	4
1	0
2	6
10	0
10	0
12	0
17	18
6	0
4	2
21	3
0	0
15	0
1	13
14	25
7	0
19	0
6	5
14	0
26	0
0	0
0	0
0	0
0	0
0	15
2	0
8	0
20	4
7	2
1	0
0	0
13	10
0	0
19	0
0	30
0	2
6	1
0	0
1	0
6	2
30	0
0	0
5	0
15	6
0	0
6	9
0	2
14	0
21	0
0	30
16	0
30	8
15	25
30	0
9	2
0	10
0	10
8	0
29	10
21	0
6	0
0	0
6	21




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232405&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]5 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=232405&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232405&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 time5 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Two Sample t-test (paired)
Difference: Mean1 - Mean24.48666666666667
t-stat7.96741547445794
df299
p-value3.43118957788204e-14
H0 value0
Alternativetwo.sided
CI Level0.95
CI[3.37847236239738,5.59486097093596]
F-test to compare two variances
F-stat1.81241663854655
df299
p-value3.39743653654523e-07
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.4441674705661,2.27456589255035]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & 4.48666666666667 \tabularnewline
t-stat & 7.96741547445794 \tabularnewline
df & 299 \tabularnewline
p-value & 3.43118957788204e-14 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [3.37847236239738,5.59486097093596] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.81241663854655 \tabularnewline
df & 299 \tabularnewline
p-value & 3.39743653654523e-07 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.4441674705661,2.27456589255035] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232405&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]4.48666666666667[/C][/ROW]
[ROW][C]t-stat[/C][C]7.96741547445794[/C][/ROW]
[ROW][C]df[/C][C]299[/C][/ROW]
[ROW][C]p-value[/C][C]3.43118957788204e-14[/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][3.37847236239738,5.59486097093596][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.81241663854655[/C][/ROW]
[ROW][C]df[/C][C]299[/C][/ROW]
[ROW][C]p-value[/C][C]3.39743653654523e-07[/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][1.4441674705661,2.27456589255035][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232405&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232405&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 - Mean24.48666666666667
t-stat7.96741547445794
df299
p-value3.43118957788204e-14
H0 value0
Alternativetwo.sided
CI Level0.95
CI[3.37847236239738,5.59486097093596]
F-test to compare two variances
F-stat1.81241663854655
df299
p-value3.39743653654523e-07
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.4441674705661,2.27456589255035]







Welch Two Sample t-test (paired)
Difference: Mean1 - Mean24.48666666666667
t-stat7.96741547445794
df299
p-value3.43118957788204e-14
H0 value0
Alternativetwo.sided
CI Level0.95
CI[3.37847236239738,5.59486097093596]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & 4.48666666666667 \tabularnewline
t-stat & 7.96741547445794 \tabularnewline
df & 299 \tabularnewline
p-value & 3.43118957788204e-14 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [3.37847236239738,5.59486097093596] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232405&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]4.48666666666667[/C][/ROW]
[ROW][C]t-stat[/C][C]7.96741547445794[/C][/ROW]
[ROW][C]df[/C][C]299[/C][/ROW]
[ROW][C]p-value[/C][C]3.43118957788204e-14[/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][3.37847236239738,5.59486097093596][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232405&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232405&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 - Mean24.48666666666667
t-stat7.96741547445794
df299
p-value3.43118957788204e-14
H0 value0
Alternativetwo.sided
CI Level0.95
CI[3.37847236239738,5.59486097093596]







Wicoxon rank sum test with continuity correction (paired)
W22606.5
p-value1.08257549761783e-14
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.336666666666667
p-value3.44169137633799e-15
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.456666666666667
p-value0

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 22606.5 \tabularnewline
p-value & 1.08257549761783e-14 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.336666666666667 \tabularnewline
p-value & 3.44169137633799e-15 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.456666666666667 \tabularnewline
p-value & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232405&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]22606.5[/C][/ROW]
[ROW][C]p-value[/C][C]1.08257549761783e-14[/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]0.336666666666667[/C][/ROW]
[ROW][C]p-value[/C][C]3.44169137633799e-15[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.456666666666667[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232405&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232405&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)
W22606.5
p-value1.08257549761783e-14
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.336666666666667
p-value3.44169137633799e-15
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.456666666666667
p-value0



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 = paired ; par6 = 0.0 ;
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')