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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 computationWed, 10 Dec 2014 15:48:36 +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/10/t1418226530sk43f40azj0s4wc.htm/, Retrieved Sun, 19 May 2024 13:56:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265431, Retrieved Sun, 19 May 2024 13:56:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79

Tree of Dependent Computations

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] [] [2014-12-10 15:23:49] [fa1b8827d7de91b8b87087311d3d9fa1]
- R     [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-10 15:42:52] [fa1b8827d7de91b8b87087311d3d9fa1]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-10 15:48:36] [c4557137b9b718365486b3b7af9cd43b] [Current]
- RMP         [Notched Boxplots] [] [2014-12-10 15:59:03] [fa1b8827d7de91b8b87087311d3d9fa1]
-    D        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-10 16:01:36] [fa1b8827d7de91b8b87087311d3d9fa1]
-    D        [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-10 16:01:36] [fa1b8827d7de91b8b87087311d3d9fa1]
- RMP           [Notched Boxplots] [] [2014-12-10 16:06:49] [fa1b8827d7de91b8b87087311d3d9fa1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
50	72
62	61
54	68
71	61
54	64
65	65
73	69
52	63
84	75
42	63
66	73
65	75
78	63
73	63
75	62
66	64
70	60
81	56
71	59
69	68
71	66
72	73
68	72
70	71
67	59
76	64
70	66
60	78
72	68
69	73
71	62
62	65
70	68
58	65
76	60
52	71
59	65
68	68
76	64
67	74
59	69
76	76
60	68
63	72
70	67
66	63
64	59
70	73
75	66
61	62
60	69
73	66
61	57
66	56
59	71
64	56
78	62
67	59
66	57
71	66
51	63
56	69
67	48
69	66
55	73
63	67
67	61
65	68
47	75
76	62
64	69
68	74
64	63
65	58
63	58
60	72
68	62
72	62
70	65
61	69
61	66
62	72
71	62
71	75
51	58
70	66
73	55
76	47
68	62
48	64
52	64
60	50
59	70
57	69
79	48
60	73
60	74
59	66
61	78
71	60
58	69
59	65
58	78
60	63
55	71
62	80
69	73
68	69
72	84
19	64
68	58
79	59
71	78
71	67
74	60
75	66
53	74
70	72
78	55
59	49
72	74
70	53
63	64
74	65
67	57
66	51
62	80
73	67
67	70
61	74
74	75
32	70
69	69
57	65
60	71
68	65
68	
73	
69	
65	
81	
55

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265431&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265431&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265431&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 165.0774647887324
Mean of Sample 265.8521126760563
t-stat-0.799214185539038
df282
p-value0.424838862827288
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.68255461332625,1.13325883867837]
F-test to compare two variances
F-stat1.69566165183613
df141
p-value0.00185928320600426
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.21727780273944,2.36204786700041]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 65.0774647887324 \tabularnewline
Mean of Sample 2 & 65.8521126760563 \tabularnewline
t-stat & -0.799214185539038 \tabularnewline
df & 282 \tabularnewline
p-value & 0.424838862827288 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-2.68255461332625,1.13325883867837] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.69566165183613 \tabularnewline
df & 141 \tabularnewline
p-value & 0.00185928320600426 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.21727780273944,2.36204786700041] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265431&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]65.0774647887324[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]65.8521126760563[/C][/ROW]
[ROW][C]t-stat[/C][C]-0.799214185539038[/C][/ROW]
[ROW][C]df[/C][C]282[/C][/ROW]
[ROW][C]p-value[/C][C]0.424838862827288[/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][-2.68255461332625,1.13325883867837][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.69566165183613[/C][/ROW]
[ROW][C]df[/C][C]141[/C][/ROW]
[ROW][C]p-value[/C][C]0.00185928320600426[/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][1.21727780273944,2.36204786700041][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265431&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265431&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 165.0774647887324
Mean of Sample 265.8521126760563
t-stat-0.799214185539038
df282
p-value0.424838862827288
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.68255461332625,1.13325883867837]
F-test to compare two variances
F-stat1.69566165183613
df141
p-value0.00185928320600426
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.21727780273944,2.36204786700041]






Welch Two Sample t-test (unpaired)
Mean of Sample 165.0774647887324
Mean of Sample 265.8521126760563
t-stat-0.799214185539038
df264.39186137137
p-value0.424883623657165
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.68310239915031,1.13380662450244]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 65.0774647887324 \tabularnewline
Mean of Sample 2 & 65.8521126760563 \tabularnewline
t-stat & -0.799214185539038 \tabularnewline
df & 264.39186137137 \tabularnewline
p-value & 0.424883623657165 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-2.68310239915031,1.13380662450244] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265431&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]65.0774647887324[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]65.8521126760563[/C][/ROW]
[ROW][C]t-stat[/C][C]-0.799214185539038[/C][/ROW]
[ROW][C]df[/C][C]264.39186137137[/C][/ROW]
[ROW][C]p-value[/C][C]0.424883623657165[/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][-2.68310239915031,1.13380662450244][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265431&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265431&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 165.0774647887324
Mean of Sample 265.8521126760563
t-stat-0.799214185539038
df264.39186137137
p-value0.424883623657165
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.68310239915031,1.13380662450244]






Wicoxon rank sum test with continuity correction (unpaired)
W9899.5
p-value0.792371385530908
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0915492957746479
p-value0.591279867454474
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0985915492957747
p-value0.495021081900117

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 9899.5 \tabularnewline
p-value & 0.792371385530908 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.0915492957746479 \tabularnewline
p-value & 0.591279867454474 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0985915492957747 \tabularnewline
p-value & 0.495021081900117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265431&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]9899.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.792371385530908[/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]0.0915492957746479[/C][/ROW]
[ROW][C]p-value[/C][C]0.591279867454474[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0985915492957747[/C][/ROW]
[ROW][C]p-value[/C][C]0.495021081900117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265431&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265431&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)
W9899.5
p-value0.792371385530908
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0915492957746479
p-value0.591279867454474
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0985915492957747
p-value0.495021081900117


Figures (Output of Computation)

Input Parameters & R Code

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):
par6 <- '0.0'
par5 <- 'unpaired'
par4 <- 'two.sided'
par3 <- '0.95'
par2 <- '2'
par1 <- '1'
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')