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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 computationSat, 06 Dec 2014 14:57:10 +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/06/t1417878028p3q5a2bte6y3kh8.htm/, Retrieved Thu, 16 May 2024 08:36:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263632, Retrieved Thu, 16 May 2024 08:36:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

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] [Two Sample] [2014-10-24 14:30:44] [5c51c91cab622bcf955f01721b682696]
-   PD    [Paired and Unpaired Two Samples Tests about the Mean] [Totale motivatie ...] [2014-12-06 14:57:10] [4ce2356216df8db4950cd852fec912aa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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56 51
57 57
51 37
56 67
30 43
61 52
47 52
56 43
50 84
67 67
41 49
45 70
48 52
44 58
37 68
56 43
66 56
38 74
34 65
49 63
55 58
49 57
59 63
40 53
58 64
60 53
63 29
56 54
54 51
52 58
34 43
69 51
32 53
48 54
67 61
58 47
57 39
42 48
64 50
58 35
66 68
26 49
61 67
52 43
51 62
55 57
50 54
60 61
56 56
63 41
61 43
52 53
55 66
72 58
33 46
66 51
66 51
64 45
40 37
46 59
58 42
51 66
50 53
52 52
54 16
66 46
61 56
80 50
51 59
56 60
53 52
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47 47
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63 52
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43 55
38 41
56 73
45 51
50 52
54 50
55 51
37 60
46 56
51 56
64 29
47 73
62 55
67 43
56 61
65 56
50 56
57 47
47 25
47 46
57 51
50 48
22 47
59 58
56 51
53 55
42 57
52 60
54 56
44 49
62 43
53 59
50 58
36 53
76 48
66 51
62 59
59 62
47 51
55 64
58 52
60 50
57 54
45 58
49 63
62 31
56 71
60 54
67 43
52 41
52 63
53 63
45 56
47 51
41 41
53 66
34 44
45 58
44 51
60 57
53 30
53 46
51 51
65 56
51 58
49 44
58 14
62 53
52 42
50 44
53 30
62 46
66 50
50 54
58 48
53 55
59 35
58 55
52 41
58 59
71 54
58 66
46 55
64 45
67 51
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69 42
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38 53
59 41
47 55
57 55
51 46
67 63
43 43
41 65
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64 39
50 44
59 57
55 69
59 46
58 46
41 40
77 70
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62 77
60 60
56 50
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56 69
65 60
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62 39
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49 49
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67 56
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58 45
NA 52
NA 68
NA 45
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NA 69
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NA 39
NA 54
NA 41
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NA 63
NA 57
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NA 51
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NA 54
NA 52
NA 59
NA 53

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263632&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263632&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263632&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'George Udny Yule' @ yule.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 154.09375
Mean of Sample 252.6861313868613
t-stat1.54731221213145
df496
p-value0.122425759919747
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.379758432113963,3.19499565839134]
F-test to compare two variances
F-stat0.886300381740631
df223
p-value0.348190166540619
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.690824019571512,1.1407462359213]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 54.09375 \tabularnewline
Mean of Sample 2 & 52.6861313868613 \tabularnewline
t-stat & 1.54731221213145 \tabularnewline
df & 496 \tabularnewline
p-value & 0.122425759919747 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.379758432113963,3.19499565839134] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.886300381740631 \tabularnewline
df & 223 \tabularnewline
p-value & 0.348190166540619 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.690824019571512,1.1407462359213] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263632&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]54.09375[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]52.6861313868613[/C][/ROW]
[ROW][C]t-stat[/C][C]1.54731221213145[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]0.122425759919747[/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][-0.379758432113963,3.19499565839134][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.886300381740631[/C][/ROW]
[ROW][C]df[/C][C]223[/C][/ROW]
[ROW][C]p-value[/C][C]0.348190166540619[/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][0.690824019571512,1.1407462359213][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263632&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263632&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 154.09375
Mean of Sample 252.6861313868613
t-stat1.54731221213145
df496
p-value0.122425759919747
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.379758432113963,3.19499565839134]
F-test to compare two variances
F-stat0.886300381740631
df223
p-value0.348190166540619
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.690824019571512,1.1407462359213]






Welch Two Sample t-test (unpaired)
Mean of Sample 154.09375
Mean of Sample 252.6861313868613
t-stat1.55672371469585
df486.210047046381
p-value0.120186740809848
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.369039968053533,3.18427719433091]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 54.09375 \tabularnewline
Mean of Sample 2 & 52.6861313868613 \tabularnewline
t-stat & 1.55672371469585 \tabularnewline
df & 486.210047046381 \tabularnewline
p-value & 0.120186740809848 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.369039968053533,3.18427719433091] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263632&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]54.09375[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]52.6861313868613[/C][/ROW]
[ROW][C]t-stat[/C][C]1.55672371469585[/C][/ROW]
[ROW][C]df[/C][C]486.210047046381[/C][/ROW]
[ROW][C]p-value[/C][C]0.120186740809848[/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][-0.369039968053533,3.18427719433091][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263632&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263632&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 154.09375
Mean of Sample 252.6861313868613
t-stat1.55672371469585
df486.210047046381
p-value0.120186740809848
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.369039968053533,3.18427719433091]






Wicoxon rank sum test with continuity correction (unpaired)
W33119.5
p-value0.127819990716562
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.084332638164755
p-value0.344701613279593
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0684632429614181
p-value0.610276642774124

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 33119.5 \tabularnewline
p-value & 0.127819990716562 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.084332638164755 \tabularnewline
p-value & 0.344701613279593 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0684632429614181 \tabularnewline
p-value & 0.610276642774124 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263632&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]33119.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.127819990716562[/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]0.084332638164755[/C][/ROW]
[ROW][C]p-value[/C][C]0.344701613279593[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0684632429614181[/C][/ROW]
[ROW][C]p-value[/C][C]0.610276642774124[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263632&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263632&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)
W33119.5
p-value0.127819990716562
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.084332638164755
p-value0.344701613279593
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0684632429614181
p-value0.610276642774124


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = black ;
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')