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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 computationSun, 14 Dec 2014 14:04:14 +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/14/t1418566154cu768c5ffrdl1sq.htm/, Retrieved Thu, 16 May 2024 06:10:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267595, Retrieved Thu, 16 May 2024 06:10:03 +0000
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-       [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-14 14:04:14] [c7f962214140f976f2c4b1bb2571d9df] [Current]
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Dataseries X:
60.42 55.94
54.89 52.36
52.16 52.42
52.97 49.97
50.84 49.90
48.03 49.53
48.13 48.29
46.65 49.84
45.90 44.63
47.16 43.65
49.23 47.93
55.77 51.77
65.32 61.77
56.89 53.79
54.45 52.71
51.27 49.30
48.81 48.77
49.47 48.80
48.77 46.42
47.58 48.48
45.40 48.37
48.48 51.81
50.70 46.57
54.13 52.42
54.23 54.65
57.68 55.54
54.94 52.97
55.87 51.60
48.61 47.32
49.93 48.43
49.06 48.48
54.00 48.03
48.07 46.70
50.87 47.55
51.97 48.87
60.19 57.26
60.61 54.77
52.86 52.55
52.10 50.16
48.87 49.13
46.35 47.19
43.87 47.13
46.48 48.00
44.03 46.26
45.90 45.07
47.10 49.10
47.57 47.30
52.39 52.19
58.29 57.32
62.89 56.54
63.35 56.19
51.67 47.33
49.55 49.39
48.60 47.77
43.29 45.13
42.39 43.06
43.23 44.67
48.06 46.39
47.13 48.00
53.74 53.35
56.35 51.16
55.79 53.18
56.26 53.39
49.30 48.70
44.42 47.77
46.90 48.17
54.42 49.10
43.23 45.19
45.77 44.80
47.03 46.90
47.17 46.17
50.94 47.48
54.90 54.39
61.18 54.89
53.58 52.71
51.57 48.77
45.48 44.74
47.23 45.77
46.55 45.19
44.61 42.84
45.93 45.20
47.19 46.74
53.57 50.00
51.29 46.29




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267595&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267595&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267595&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Two Sample t-test (unpaired)
Mean of Sample 150.8311904761905
Mean of Sample 249.4805952380952
t-stat1.95233806916189
df166
p-value0.0525802551061847
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.0152328610503191,2.7164233372408]
F-test to compare two variances
F-stat1.85751127398815
df83
p-value0.00526510319003615
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.2044226288459,2.86473207191338]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 50.8311904761905 \tabularnewline
Mean of Sample 2 & 49.4805952380952 \tabularnewline
t-stat & 1.95233806916189 \tabularnewline
df & 166 \tabularnewline
p-value & 0.0525802551061847 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.0152328610503191,2.7164233372408] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.85751127398815 \tabularnewline
df & 83 \tabularnewline
p-value & 0.00526510319003615 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.2044226288459,2.86473207191338] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267595&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]50.8311904761905[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]49.4805952380952[/C][/ROW]
[ROW][C]t-stat[/C][C]1.95233806916189[/C][/ROW]
[ROW][C]df[/C][C]166[/C][/ROW]
[ROW][C]p-value[/C][C]0.0525802551061847[/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][-0.0152328610503191,2.7164233372408][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.85751127398815[/C][/ROW]
[ROW][C]df[/C][C]83[/C][/ROW]
[ROW][C]p-value[/C][C]0.00526510319003615[/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][1.2044226288459,2.86473207191338][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267595&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267595&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 (unpaired)
Mean of Sample 150.8311904761905
Mean of Sample 249.4805952380952
t-stat1.95233806916189
df166
p-value0.0525802551061847
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.0152328610503191,2.7164233372408]
F-test to compare two variances
F-stat1.85751127398815
df83
p-value0.00526510319003615
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.2044226288459,2.86473207191338]







Welch Two Sample t-test (unpaired)
Mean of Sample 150.8311904761905
Mean of Sample 249.4805952380952
t-stat1.95233806916189
df152.286011401237
p-value0.052732088046948
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.0161365998619184,2.71732707605239]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 50.8311904761905 \tabularnewline
Mean of Sample 2 & 49.4805952380952 \tabularnewline
t-stat & 1.95233806916189 \tabularnewline
df & 152.286011401237 \tabularnewline
p-value & 0.052732088046948 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.0161365998619184,2.71732707605239] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267595&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]50.8311904761905[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]49.4805952380952[/C][/ROW]
[ROW][C]t-stat[/C][C]1.95233806916189[/C][/ROW]
[ROW][C]df[/C][C]152.286011401237[/C][/ROW]
[ROW][C]p-value[/C][C]0.052732088046948[/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][-0.0161365998619184,2.71732707605239][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267595&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267595&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 (unpaired)
Mean of Sample 150.8311904761905
Mean of Sample 249.4805952380952
t-stat1.95233806916189
df152.286011401237
p-value0.052732088046948
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.0161365998619184,2.71732707605239]







Wicoxon rank sum test with continuity correction (unpaired)
W3982.5
p-value0.149803412923076
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.166666666666667
p-value0.193767083268003
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.166666666666667
p-value0.193767083268003

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 3982.5 \tabularnewline
p-value & 0.149803412923076 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.166666666666667 \tabularnewline
p-value & 0.193767083268003 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.166666666666667 \tabularnewline
p-value & 0.193767083268003 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267595&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]3982.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.149803412923076[/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]0.166666666666667[/C][/ROW]
[ROW][C]p-value[/C][C]0.193767083268003[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.166666666666667[/C][/ROW]
[ROW][C]p-value[/C][C]0.193767083268003[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267595&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267595&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 (unpaired)
W3982.5
p-value0.149803412923076
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.166666666666667
p-value0.193767083268003
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.166666666666667
p-value0.193767083268003



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):
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')