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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 computationTue, 16 Dec 2014 19:21:46 +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/16/t1418757720rpiqq76i91tntxn.htm/, Retrieved Thu, 16 May 2024 14:52:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269903, Retrieved Thu, 16 May 2024 14:52:12 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.5 149
6 139
6.5 148
1 158
1 128
5.5 224
8.5 159
6.5 105
4.5 159
2 167
5 165
0.5 159
5 119
5 176
2.5 54
5 91
5.5 163
3.5 124
3 137
4 121
0.5 153
6.5 148
4.5 221
7.5 188
5.5 149
4 244
7.5 148
7 92
4 150
5.5 153
2.5 94
5.5 156
3.5 132
2.5 161
4.5 105
4.5 97
4.5 151
6 131
2.5 166
5 157
0 111
5 145
6.5 162
5 163
6 59
4.5 187
5.5 109
1 90
7.5 105
6 83
5 116
1 42
5 148
6.5 155
7 125
4.5 116
0 128
8.5 138
3.5 49
7.5 96
3.5 164
6 162
1.5 99
9 202
3.5 186
3.5 66
4 183
6.5 214
7.5 188
6 104
5 177
5.5 126
3.5 76
7.5 99
6.5 139
6.5 162
6.5 108
7 159
3.5 74
1.5 110
4 96
7.5 116
4.5 87
0 97
3.5 127
5.5 106
5 80
4.5 74
2.5 91
7.5 133
7 74
0 114
4.5 140
3 95
1.5 98
3.5 121
2.5 126
5.5 98
8 95
1 110
5 70
4.5 102
3 86
3 130
8 96
2.5 102
7 100
0 94
1 52
3.5 98
5.5 118
5.5 99
0.5 48
7.5 50
9 150
9.5 154
8.5 109
7 68
8 194
10 158
7 159
8.5 67
9 147
9.5 39
4 100
6 111
8 138
5.5 101
9.5 131
7.5 101
7 114
7.5 165
8 114
7 111
7 75
6 82
10 121
2.5 32
9 150
8 117
6 71
8.5 165
6 154
9 126
8 149
9 145
5.5 120
7 109
5.5 132
9 172
2 169
8.5 114
9 156
8.5 172
9 68
7.5 89
10 167
9 113
7.5 115
6 78
10.5 118
8.5 87
8 173
10 2
10.5 162
6.5 49
9.5 122
8.5 96
7.5 100
5 82
8 100
10 115
7 141
7.5 165
7.5 165
9.5 110
6 118
10 158
7 146
3 49
6 90
7 121
10 155
7 104
3.5 147
8 110
10 108
5.5 113
6 115
6.5 61
6.5 60
8.5 109
4 68
9.5 111
8 77
8.5 73
5.5 151
7 89
9 78
8 110
10 220
8 65
6 141
8 117
5 122
9 63
4.5 44
8.5 52
9.5 131
8.5 101
7.5 42
7.5 152
5 107
7 77
8 154
5.5 103
8.5 96
9.5 175
7 57
8 112
8.5 143
3.5 49
6.5 110
6.5 131
10.5 167
8.5 56
8 137
10 86
10 121
9.5 149
9 168
10 140
7.5 88
4.5 168
4.5 94
0.5 51
6.5 48
4.5 145
5.5 66
5 85
6 109
4 63
8 102
10.5 162
6.5 86
8 114
8.5 164
5.5 119
7 126
5 132
3.5 142
5 83
9 94
8.5 81
5 166
9.5 110
3 64
1.5 93
6 104
0.5 105
6.5 49
7.5 88
4.5 95
8 102
9 99
7.5 63
8.5 76
7 109
9.5 117
6.5 57
9.5 120
6 73
8 91
9.5 108
8 105
8 117
9 119

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=269903&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=269903&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269903&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 (paired)
Difference: Mean1 - Mean2-110.523465703971
t-stat-46.7018854294005
df276
p-value4.72822370192026e-133
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-115.182294540261,-105.864636867681]
F-test to compare two variances
F-stat0.00411075616534285
df276
p-value9.96289634924833e-249
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.00324516752556598,0.00520722462485416]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -110.523465703971 \tabularnewline
t-stat & -46.7018854294005 \tabularnewline
df & 276 \tabularnewline
p-value & 4.72822370192026e-133 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-115.182294540261,-105.864636867681] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.00411075616534285 \tabularnewline
df & 276 \tabularnewline
p-value & 9.96289634924833e-249 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.00324516752556598,0.00520722462485416] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269903&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-110.523465703971[/C][/ROW]
[ROW][C]t-stat[/C][C]-46.7018854294005[/C][/ROW]
[ROW][C]df[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]4.72822370192026e-133[/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][-115.182294540261,-105.864636867681][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.00411075616534285[/C][/ROW]
[ROW][C]df[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]9.96289634924833e-249[/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][0.00324516752556598,0.00520722462485416][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269903&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269903&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 (paired)
Difference: Mean1 - Mean2-110.523465703971
t-stat-46.7018854294005
df276
p-value4.72822370192026e-133
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-115.182294540261,-105.864636867681]
F-test to compare two variances
F-stat0.00411075616534285
df276
p-value9.96289634924833e-249
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.00324516752556598,0.00520722462485416]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-110.523465703971
t-stat-46.7018854294005
df276
p-value4.72822370192026e-133
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-115.182294540261,-105.864636867681]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -110.523465703971 \tabularnewline
t-stat & -46.7018854294005 \tabularnewline
df & 276 \tabularnewline
p-value & 4.72822370192026e-133 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-115.182294540261,-105.864636867681] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269903&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-110.523465703971[/C][/ROW]
[ROW][C]t-stat[/C][C]-46.7018854294005[/C][/ROW]
[ROW][C]df[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]4.72822370192026e-133[/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][-115.182294540261,-105.864636867681][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269903&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269903&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 (paired)
Difference: Mean1 - Mean2-110.523465703971
t-stat-46.7018854294005
df276
p-value4.72822370192026e-133
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-115.182294540261,-105.864636867681]






Wicoxon rank sum test with continuity correction (paired)
W1
p-value3.5762945921478e-47
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.996389891696751
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.472924187725632
p-value0

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 1 \tabularnewline
p-value & 3.5762945921478e-47 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.996389891696751 \tabularnewline
p-value & 0 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.472924187725632 \tabularnewline
p-value & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269903&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]1[/C][/ROW]
[ROW][C]p-value[/C][C]3.5762945921478e-47[/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]0.996389891696751[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.472924187725632[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269903&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269903&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 (paired)
W1
p-value3.5762945921478e-47
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.996389891696751
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.472924187725632
p-value0


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0.0 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; 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')