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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 computationThu, 11 Dec 2014 13:23:37 +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/11/t14183042674uk5gov60lihxw5.htm/, Retrieved Sun, 19 May 2024 17:12:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265967, Retrieved Sun, 19 May 2024 17:12:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

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-       [Paired and Unpaired Two Samples Tests about the Mean] [Two sample T-test...] [2014-12-11 13:23:37] [d71ad52285d92a63edfc83f9fb1da7a1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 11.3
7.4 9.6
12.2 16.1
12.8 13.4
7.4 12.7
6.7 12.3
12.6 7.9
14.8 12.3
13.3 11.6
11.1 6.7
8.2 12.1
11.4 5.7
6.4 8
10.6 13.3
12 9.1
6.3 12.2
11.9 8.8
9.3 14.6
10 12.6
6.4 9.9
13.8 10.5
10.8 13.4
13.8 10.9
11.7 4.3
10.9 10.3
9.9 11.8
11.5 11.2
8.3 11.4
11.7 8.6
6.1 13.2
9 12.6
9.7 5.6
10.8 9.9
10.3 8.8
10.4 7.7
9.3 9
11.8 7.3
5.9 11.4
11.4 13.6
13 7.9
10.8 10.7
11.3 10.3
11.8 8.3
12.7 9.6
10.9 14.2
13.3 8.5
10.1 13.5
14.3 4.9
9.3 6.4
12.5 9.6
7.6 11.6
15.9 11.1
9.2 16.6
11.1 12.6
13 18.9
14.5 11.6
12.3 14.6
11.4 13.85
7.3 14.85
12.6 11.75
NA 18.45
13 15.9
13.2 19.9
7.7 10.95
4.35 18.45
12.7 15.1
18.1 15
17.85 11.35
17.1 15.95
19.1 18.1
16.1 14.6
13.35 17.6
18.4 15.35
14.7 13.4
10.6 13.9
12.6 15.25
16.2 12.9
13.6 16.1
14.1 17.35
14.5 13.15
16.15 12.15
14.75 12.6
14.8 10.35
12.45 15.4
12.65 9.6
17.35 18.2
8.6 13.6
18.4 14.85
16.1 14.1
17.75 14.9
15.25 16.25
17.65 13.6
15.6 15.65
16.35 14.6
17.65 12.65
13.6 11.9
11.7 19.2
14.35 16.6
14.75 11.2
18.25 13.2
9.9 15.85
16 11.15
18.25 15.65
16.85 7.65
18.95 15.2
15.6 15.6
17.1 13.1
16.1 11.85
15.4 12.4
15.4 11.4
13.35 14.9
19.1 19.9
7.6 11.2
19.1 14.6
14.75 14.75
19.25 15.15
13.6 16.85
12.75 7.85
9.85 12.6
15.25 7.85
11.9 10.95
16.35 12.35
12.4 9.95
14.35 14.9
18.15 16.65
17.75 13.4
12.35 13.95
15.6 15.7
19.3 16.85
17.1 10.95
18.4 15.35
19.05 12.2
18.55 15.1
19.1 17.75
12.85 15.2
9.5 16.65
4.5 8.1
13.6 NA
11.7 NA
13.35 NA
17.75 NA
17.6 NA
14.05 NA
16.1 NA
13.35 NA
11.85 NA
11.95 NA
13.2 NA
7.7 NA
14.6 NA

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265967&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265967&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265967&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 time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 113.1224832214765
Mean of Sample 212.729197080292
t-stat0.971066326432705
df284
p-value0.332341552077774
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.403905156443477,1.19047743881256]
F-test to compare two variances
F-stat1.16707775269311
df148
p-value0.360560085390348
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.837576527845938,1.62240689532013]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 13.1224832214765 \tabularnewline
Mean of Sample 2 & 12.729197080292 \tabularnewline
t-stat & 0.971066326432705 \tabularnewline
df & 284 \tabularnewline
p-value & 0.332341552077774 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.403905156443477,1.19047743881256] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.16707775269311 \tabularnewline
df & 148 \tabularnewline
p-value & 0.360560085390348 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.837576527845938,1.62240689532013] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265967&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]13.1224832214765[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.729197080292[/C][/ROW]
[ROW][C]t-stat[/C][C]0.971066326432705[/C][/ROW]
[ROW][C]df[/C][C]284[/C][/ROW]
[ROW][C]p-value[/C][C]0.332341552077774[/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][-0.403905156443477,1.19047743881256][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.16707775269311[/C][/ROW]
[ROW][C]df[/C][C]148[/C][/ROW]
[ROW][C]p-value[/C][C]0.360560085390348[/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][0.837576527845938,1.62240689532013][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265967&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265967&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 113.1224832214765
Mean of Sample 212.729197080292
t-stat0.971066326432705
df284
p-value0.332341552077774
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.403905156443477,1.19047743881256]
F-test to compare two variances
F-stat1.16707775269311
df148
p-value0.360560085390348
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.837576527845938,1.62240689532013]






Welch Two Sample t-test (unpaired)
Mean of Sample 113.1224832214765
Mean of Sample 212.729197080292
t-stat0.974223776150455
df283.98606242809
p-value0.330774539230931
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.401321634143676,1.18789391651275]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 13.1224832214765 \tabularnewline
Mean of Sample 2 & 12.729197080292 \tabularnewline
t-stat & 0.974223776150455 \tabularnewline
df & 283.98606242809 \tabularnewline
p-value & 0.330774539230931 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.401321634143676,1.18789391651275] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265967&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]13.1224832214765[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.729197080292[/C][/ROW]
[ROW][C]t-stat[/C][C]0.974223776150455[/C][/ROW]
[ROW][C]df[/C][C]283.98606242809[/C][/ROW]
[ROW][C]p-value[/C][C]0.330774539230931[/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][-0.401321634143676,1.18789391651275][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265967&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265967&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 113.1224832214765
Mean of Sample 212.729197080292
t-stat0.974223776150455
df283.98606242809
p-value0.330774539230931
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.401321634143676,1.18789391651275]






Wicoxon rank sum test with continuity correction (unpaired)
W10851
p-value0.356664048934058
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.102336746191153
p-value0.443454045285645
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0863175427423701
p-value0.662170873204011

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 10851 \tabularnewline
p-value & 0.356664048934058 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.102336746191153 \tabularnewline
p-value & 0.443454045285645 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0863175427423701 \tabularnewline
p-value & 0.662170873204011 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265967&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]10851[/C][/ROW]
[ROW][C]p-value[/C][C]0.356664048934058[/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]0.102336746191153[/C][/ROW]
[ROW][C]p-value[/C][C]0.443454045285645[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0863175427423701[/C][/ROW]
[ROW][C]p-value[/C][C]0.662170873204011[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265967&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265967&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)
W10851
p-value0.356664048934058
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.102336746191153
p-value0.443454045285645
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0863175427423701
p-value0.662170873204011


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 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')