## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_twosampletests_mean.wasp
Title produced by softwarePaired and Unpaired Two Samples Tests about the Mean
Date of computationMon, 16 Nov 2020 10:29:34 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Nov/16/t1605519347k02g05to8h1qhz7.htm/, Retrieved Wed, 21 Apr 2021 08:42:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319290, Retrieved Wed, 21 Apr 2021 08:42:51 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact23
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] [Error in computin...] [2020-11-16 09:29:34] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0.62	0.62
0.54	0.62
0.54	1.16
0.54	0.61
0.62	1.16
0.62	1.16
0.62	1.16
0.69	0.77
0.62	0.77
0.62	1.16
0.62	1.16

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319290&T=0

[TABLE]
[ROW]
 Summary of computational transaction[/C][/ROW] [ROW] Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW] Raw Output[/C] view raw output of R engine [/C][/ROW] [ROW] Computing time[/C] 1 seconds[/C][/ROW] [ROW] R Server[/C] Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319290&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319290&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server Big Analytics Cloud Computing Center

 Two Sample t-test (unpaired) Mean of Sample 1 0.604545454545454 Mean of Sample 2 0.940909090909091 t-stat -4.2675581637033 df 20 p-value 0.000376337886685354 H0 value 0 Alternative two.sided CI Level 0.95 CI [-0.500776685589684,-0.171950587137589] F-test to compare two variances F-stat 0.0324414899461597 df 10 p-value 6.94283672721897e-06 H0 value 1 Alternative two.sided CI Level 0.95 CI [0.00872835798398254,0.120578265907304]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 0.604545454545454 \tabularnewline
Mean of Sample 2 & 0.940909090909091 \tabularnewline
t-stat & -4.2675581637033 \tabularnewline
df & 20 \tabularnewline
p-value & 0.000376337886685354 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.500776685589684,-0.171950587137589] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.0324414899461597 \tabularnewline
df & 10 \tabularnewline
p-value & 6.94283672721897e-06 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.00872835798398254,0.120578265907304] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319290&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]0.604545454545454[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]0.940909090909091[/C][/ROW]
[ROW][C]t-stat[/C][C]-4.2675581637033[/C][/ROW]
[ROW][C]df[/C][C]20[/C][/ROW]
[ROW][C]p-value[/C][C]0.000376337886685354[/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][-0.500776685589684,-0.171950587137589][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.0324414899461597[/C][/ROW]
[ROW][C]df[/C][C]10[/C][/ROW]
[ROW][C]p-value[/C][C]6.94283672721897e-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][0.00872835798398254,0.120578265907304][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319290&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319290&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 1 0.604545454545454 Mean of Sample 2 0.940909090909091 t-stat -4.2675581637033 df 20 p-value 0.000376337886685354 H0 value 0 Alternative two.sided CI Level 0.95 CI [-0.500776685589684,-0.171950587137589] F-test to compare two variances F-stat 0.0324414899461597 df 10 p-value 6.94283672721897e-06 H0 value 1 Alternative two.sided CI Level 0.95 CI [0.00872835798398254,0.120578265907304]

 Welch Two Sample t-test (unpaired) Mean of Sample 1 0.604545454545454 Mean of Sample 2 0.940909090909091 t-stat -4.2675581637033 df 10.6481476557479 p-value 0.00142635874149821 H0 value 0 Alternative two.sided CI Level 0.95 CI [-0.510544507444021,-0.162182765283252]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 0.604545454545454 \tabularnewline
Mean of Sample 2 & 0.940909090909091 \tabularnewline
t-stat & -4.2675581637033 \tabularnewline
df & 10.6481476557479 \tabularnewline
p-value & 0.00142635874149821 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.510544507444021,-0.162182765283252] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319290&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]0.604545454545454[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]0.940909090909091[/C][/ROW]
[ROW][C]t-stat[/C][C]-4.2675581637033[/C][/ROW]
[ROW][C]df[/C][C]10.6481476557479[/C][/ROW]
[ROW][C]p-value[/C][C]0.00142635874149821[/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][-0.510544507444021,-0.162182765283252][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319290&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319290&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 1 0.604545454545454 Mean of Sample 2 0.940909090909091 t-stat -4.2675581637033 df 10.6481476557479 p-value 0.00142635874149821 H0 value 0 Alternative two.sided CI Level 0.95 CI [-0.510544507444021,-0.162182765283252]

 Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired) W 17 p-value 0.00307147459884264 H0 value 0 Alternative two.sided Kolmogorov-Smirnov Test to compare Distributions of two Samples KS Statistic 0.727272727272727 p-value 0.00594601124096328 Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples KS Statistic 0.545454545454545 p-value 0.0758017009854388

\begin{tabular}{lllllllll}
\hline
Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired) \tabularnewline
W & 17 \tabularnewline
p-value & 0.00307147459884264 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.727272727272727 \tabularnewline
p-value & 0.00594601124096328 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.545454545454545 \tabularnewline
p-value & 0.0758017009854388 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319290&T=3

[TABLE]
[ROW][C]Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]17[/C][/ROW]
[ROW][C]p-value[/C][C]0.00307147459884264[/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]0.727272727272727[/C][/ROW]
[ROW][C]p-value[/C][C]0.00594601124096328[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.545454545454545[/C][/ROW]
[ROW][C]p-value[/C][C]0.0758017009854388[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319290&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319290&T=3

As an alternative you can also use a QR Code:

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

 Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired) W 17 p-value 0.00307147459884264 H0 value 0 Alternative two.sided Kolmogorov-Smirnov Test to compare Distributions of two Samples KS Statistic 0.727272727272727 p-value 0.00594601124096328 Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples KS Statistic 0.545454545454545 p-value 0.0758017009854388

par1 <- as.numeric(par1) #column number of first samplepar2 <- as.numeric(par2) #column number of second samplepar3 <- as.numeric(par3) #confidence (= 1 - alpha)if (par5 == 'unpaired') paired <- FALSE else paired <- TRUEpar6 <- as.numeric(par6) #H0z <- 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 - m2newsam1 <- z[!is.na(z[,par1]),par1]newsam2 <- z[,par2]+mdiffnewsam2 <- 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)myWlabel <- 'Wilcoxon Signed-Rank Test'if (par5=='unpaired') myWlabel = 'Wilcoxon Rank-Sum Test (Mann–Whitney U test)'a<-table.element(a,paste(myWlabel,' 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')