Free Statistics

of Irreproducible Research!

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 16:09:44 +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/t1418660031h0oup2p70a84cfl.htm/, Retrieved Thu, 16 May 2024 15:08:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268701, Retrieved Thu, 16 May 2024 15:08:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact46
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] [confstatM] [2014-12-15 16:09:44] [21b927ddce509724d48ffb8407994bd0] [Current]
Feedback Forum

Post a new message
Dataseries X:
13 NA
14 NA
NA 16
NA 14
NA 13
15 NA
NA 13
NA 20
NA 17
NA 15
NA 16
17 NA
11 NA
16 NA
NA 16
15 NA
14 NA
NA 16
17 NA
NA 15
NA 14
NA 14
NA 15
17 NA
14 NA
16 NA
NA 15
NA 16
8 NA
NA 17
10 NA
NA 16
NA 16
NA 16
8 NA
NA 14
NA 16
NA 19
NA 19
NA 14
NA 13
NA 15
11 NA
9 NA
12 NA
NA 13
17 NA
7 NA
15 NA
NA 12
15 NA
NA 16
14 NA
16 NA
NA 13
16 NA
10 NA
NA 12
14 NA
16 NA
NA 18
12 NA
15 NA
NA 16
NA 16
NA 16
NA 16
12 NA
NA 15
NA 14
15 NA
NA 16
13 NA
10 NA
NA 17
NA 15
NA 18
NA 16
NA 20
NA 16
NA 17
NA 16
15 NA
NA 13
NA 16
NA 16
NA 16
NA 17
NA 20
14 NA
NA 17
NA 6
NA 16
NA 15
NA 16
16 NA
14 NA
NA 16
16 NA
16 NA
NA 14
14 NA
NA 16
NA 16
15 NA
NA 16
NA 16
NA 18
15 NA
16 NA
16 NA
16 NA
NA 17
14 NA
NA 18
9 NA
NA 15
14 NA
NA 15
13 NA
16 NA
NA 20
14 NA
NA 12
NA 15
NA 15
NA 15
NA 16
11 NA
NA 16
7 NA
11 NA
9 NA
NA 15
16 NA
NA 14
15 NA
13 NA
13 NA
12 NA
NA 16
NA 14
NA 16
NA 14
15 NA
10 NA
NA 16
14 NA
16 NA
12 NA
16 NA
NA 16
NA 15
14 NA
16 NA
NA 11
15 NA
NA 18
NA 13
7 NA
NA 7
NA 17
NA 18
15 NA
8 NA
13 NA
NA 13
NA 15
NA 18
NA 16
14 NA
15 NA
19 NA
NA 16
NA 12
16 NA
11 NA
16 NA
NA 15
NA 19
15 NA
14 NA
14 NA
NA 17
NA 16
NA 20
NA 16
9 NA
NA 13
NA 15
NA 19
16 NA
17 NA
NA 16
9 NA
NA 11
NA 14
19 NA
NA 13
14 NA
NA 15
NA 15
14 NA
NA 16
17 NA
NA 12
15 NA
NA 17
15 NA
10 NA
NA 16
NA 15
11 NA
NA 16
NA 16
16 NA
NA 14
14 NA
16 NA
NA 16
NA 18
14 NA
NA 20
15 NA
16 NA
NA 16
16 NA
12 NA
NA 8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268701&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268701&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268701&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'Herman Ole Andreas Wold' @ wold.wessa.net







Two Sample t-test (unpaired)
Mean of Sample 115.4444444444444
Mean of Sample 213.7281553398058
t-stat5.16680298631467
df227
p-value2.60532844222022e-07
H0 value0
Alternativegreater
CI Level0.95
CI[1.16766887591499,Inf]
F-test to compare two variances
F-stat0.727616129727865
df125
p-value0.0904002330202174
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.499939348115413,1.05150105695259]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 15.4444444444444 \tabularnewline
Mean of Sample 2 & 13.7281553398058 \tabularnewline
t-stat & 5.16680298631467 \tabularnewline
df & 227 \tabularnewline
p-value & 2.60532844222022e-07 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & greater \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.16766887591499,Inf] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.727616129727865 \tabularnewline
df & 125 \tabularnewline
p-value & 0.0904002330202174 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.499939348115413,1.05150105695259] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268701&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]15.4444444444444[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.7281553398058[/C][/ROW]
[ROW][C]t-stat[/C][C]5.16680298631467[/C][/ROW]
[ROW][C]df[/C][C]227[/C][/ROW]
[ROW][C]p-value[/C][C]2.60532844222022e-07[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]greater[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][1.16766887591499,Inf][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.727616129727865[/C][/ROW]
[ROW][C]df[/C][C]125[/C][/ROW]
[ROW][C]p-value[/C][C]0.0904002330202174[/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][0.499939348115413,1.05150105695259][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268701&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268701&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 115.4444444444444
Mean of Sample 213.7281553398058
t-stat5.16680298631467
df227
p-value2.60532844222022e-07
H0 value0
Alternativegreater
CI Level0.95
CI[1.16766887591499,Inf]
F-test to compare two variances
F-stat0.727616129727865
df125
p-value0.0904002330202174
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.499939348115413,1.05150105695259]







Welch Two Sample t-test (unpaired)
Mean of Sample 115.4444444444444
Mean of Sample 213.7281553398058
t-stat5.08526225264763
df201.309146240585
p-value4.1888328608408e-07
H0 value0
Alternativegreater
CI Level0.95
CI[1.1585802436906,Inf]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 15.4444444444444 \tabularnewline
Mean of Sample 2 & 13.7281553398058 \tabularnewline
t-stat & 5.08526225264763 \tabularnewline
df & 201.309146240585 \tabularnewline
p-value & 4.1888328608408e-07 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & greater \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.1585802436906,Inf] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268701&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]15.4444444444444[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.7281553398058[/C][/ROW]
[ROW][C]t-stat[/C][C]5.08526225264763[/C][/ROW]
[ROW][C]df[/C][C]201.309146240585[/C][/ROW]
[ROW][C]p-value[/C][C]4.1888328608408e-07[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]greater[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][1.1585802436906,Inf][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268701&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268701&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 115.4444444444444
Mean of Sample 213.7281553398058
t-stat5.08526225264763
df201.309146240585
p-value4.1888328608408e-07
H0 value0
Alternativegreater
CI Level0.95
CI[1.1585802436906,Inf]







Wicoxon rank sum test with continuity correction (unpaired)
W8901.5
p-value4.27204796265384e-07
H0 value0
Alternativegreater
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.00793650793650794
p-value0.992886033493933
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.253505933117584
p-value0.000686335296596393

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 8901.5 \tabularnewline
p-value & 4.27204796265384e-07 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & greater \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.00793650793650794 \tabularnewline
p-value & 0.992886033493933 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.253505933117584 \tabularnewline
p-value & 0.000686335296596393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268701&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]8901.5[/C][/ROW]
[ROW][C]p-value[/C][C]4.27204796265384e-07[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]greater[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributions of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.00793650793650794[/C][/ROW]
[ROW][C]p-value[/C][C]0.992886033493933[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.253505933117584[/C][/ROW]
[ROW][C]p-value[/C][C]0.000686335296596393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268701&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268701&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)
W8901.5
p-value4.27204796265384e-07
H0 value0
Alternativegreater
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.00793650793650794
p-value0.992886033493933
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.253505933117584
p-value0.000686335296596393



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