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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, 17 Dec 2014 16:10:32 +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/17/t1418832640rbz3o6xgmjf7bb9.htm/, Retrieved Thu, 16 May 2024 07:56:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270484, Retrieved Thu, 16 May 2024 07:56:23 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
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] [] [2014-12-17 16:10:32] [d6e8bf517fe66b8503604aeb9a6628d3] [Current]
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Dataseries X:
'FALSE' 149
139 "'FALSE'"
'FALSE' 148
158 "'FALSE'"
128 "'FALSE'"
224 "'FALSE'"
'FALSE' 159
105 "'FALSE'"
159 "'FALSE'"
167 "'FALSE'"
165 "'FALSE'"
159 "'FALSE'"
119 "'FALSE'"
'FALSE' 176
'FALSE' 54
'FALSE' 91
163 "'FALSE'"
'FALSE' 124
137 "'FALSE'"
'FALSE' 121
153 "'FALSE'"
148 "'FALSE'"
'FALSE' 221
188 "'FALSE'"
149 "'FALSE'"
244 "'FALSE'"
148 "'FALSE'"
'FALSE' 92
150 "'FALSE'"
'FALSE' 153
'FALSE' 94
'FALSE' 156
132 "'FALSE'"
161 "'FALSE'"
105 "'FALSE'"
97 "'FALSE'"
'FALSE' 151
131 "'FALSE'"
166 "'FALSE'"
'FALSE' 157
111 "'FALSE'"
145 "'FALSE'"
162 "'FALSE'"
163 "'FALSE'"
59 "'FALSE'"
'FALSE' 187
109 "'FALSE'"
90 "'FALSE'"
'FALSE' 105
83 "'FALSE'"
116 "'FALSE'"
42 "'FALSE'"
148 "'FALSE'"
155 "'FALSE'"
125 "'FALSE'"
116 "'FALSE'"
'FALSE' 128
138 "'FALSE'"
'FALSE' 49
96 "'FALSE'"
164 "'FALSE'"
'FALSE' 162
'FALSE' 99
202 "'FALSE'"
'FALSE' 186
66 "'FALSE'"
'FALSE' 183
214 "'FALSE'"
188 "'FALSE'"
'FALSE' 104
'FALSE' 177
'FALSE' 126
'FALSE' 76
99 "'FALSE'"
'FALSE' 139
78 "'FALSE'"
'FALSE' 162
108 "'FALSE'"
'FALSE' 159
'FALSE' 74
110 "'FALSE'"
'FALSE' 96
'FALSE' 116
'FALSE' 87
97 "'FALSE'"
'FALSE' 127
106 "'FALSE'"
80 "'FALSE'"
'FALSE' 74
'FALSE' 91
'FALSE' 133
74 "'FALSE'"
114 "'FALSE'"
140 "'FALSE'"
'FALSE' 95
98 "'FALSE'"
'FALSE' 121
126 "'FALSE'"
98 "'FALSE'"
95 "'FALSE'"
110 "'FALSE'"
70 "'FALSE'"
'FALSE' 102
86 "'FALSE'"
130 "'FALSE'"
96 "'FALSE'"
'FALSE' 102
'FALSE' 100
'FALSE' 94
'FALSE' 52
'FALSE' 98
'FALSE' 118
99 "'FALSE'"




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270484&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]4 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=270484&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270484&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Two Sample t-test (unpaired)
Mean of Sample 1128.80303030303
Mean of Sample 2122.723404255319
t-stat0.667997152774701
df111
p-value0.505522005122019
H0 value1
Alternativetwo.sided
CI Level0.95
CI[-8.98872876893143,21.1479808643537]
F-test to compare two variances
F-stat1.03800135841812
df65
p-value0.904073194547234
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.597396026723097,1.75869403795495]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 128.80303030303 \tabularnewline
Mean of Sample 2 & 122.723404255319 \tabularnewline
t-stat & 0.667997152774701 \tabularnewline
df & 111 \tabularnewline
p-value & 0.505522005122019 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-8.98872876893143,21.1479808643537] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.03800135841812 \tabularnewline
df & 65 \tabularnewline
p-value & 0.904073194547234 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.597396026723097,1.75869403795495] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270484&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]128.80303030303[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]122.723404255319[/C][/ROW]
[ROW][C]t-stat[/C][C]0.667997152774701[/C][/ROW]
[ROW][C]df[/C][C]111[/C][/ROW]
[ROW][C]p-value[/C][C]0.505522005122019[/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][-8.98872876893143,21.1479808643537][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.03800135841812[/C][/ROW]
[ROW][C]df[/C][C]65[/C][/ROW]
[ROW][C]p-value[/C][C]0.904073194547234[/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][0.597396026723097,1.75869403795495][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270484&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270484&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 1128.80303030303
Mean of Sample 2122.723404255319
t-stat0.667997152774701
df111
p-value0.505522005122019
H0 value1
Alternativetwo.sided
CI Level0.95
CI[-8.98872876893143,21.1479808643537]
F-test to compare two variances
F-stat1.03800135841812
df65
p-value0.904073194547234
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.597396026723097,1.75869403795495]







Welch Two Sample t-test (unpaired)
Mean of Sample 1128.80303030303
Mean of Sample 2122.723404255319
t-stat0.670113640487854
df100.339752398693
p-value0.504324671333904
H0 value1
Alternativetwo.sided
CI Level0.95
CI[-8.95874199216354,21.1179940875859]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 128.80303030303 \tabularnewline
Mean of Sample 2 & 122.723404255319 \tabularnewline
t-stat & 0.670113640487854 \tabularnewline
df & 100.339752398693 \tabularnewline
p-value & 0.504324671333904 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-8.95874199216354,21.1179940875859] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270484&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]128.80303030303[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]122.723404255319[/C][/ROW]
[ROW][C]t-stat[/C][C]0.670113640487854[/C][/ROW]
[ROW][C]df[/C][C]100.339752398693[/C][/ROW]
[ROW][C]p-value[/C][C]0.504324671333904[/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][-8.95874199216354,21.1179940875859][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270484&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270484&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 1128.80303030303
Mean of Sample 2122.723404255319
t-stat0.670113640487854
df100.339752398693
p-value0.504324671333904
H0 value1
Alternativetwo.sided
CI Level0.95
CI[-8.95874199216354,21.1179940875859]







Wicoxon rank sum test with continuity correction (unpaired)
W1666
p-value0.504726391359508
H0 value1
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.137653127014829
p-value0.675681603345754
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0915538362346873
p-value0.975474137416984

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 1666 \tabularnewline
p-value & 0.504726391359508 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.137653127014829 \tabularnewline
p-value & 0.675681603345754 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0915538362346873 \tabularnewline
p-value & 0.975474137416984 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270484&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]1666[/C][/ROW]
[ROW][C]p-value[/C][C]0.504726391359508[/C][/ROW]
[ROW][C]H0 value[/C][C]1[/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]0.137653127014829[/C][/ROW]
[ROW][C]p-value[/C][C]0.675681603345754[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0915538362346873[/C][/ROW]
[ROW][C]p-value[/C][C]0.975474137416984[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270484&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270484&T=3

As an alternative you can also use a QR Code:  

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

Wicoxon rank sum test with continuity correction (unpaired)
W1666
p-value0.504726391359508
H0 value1
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.137653127014829
p-value0.675681603345754
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0915538362346873
p-value0.975474137416984



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