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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 computationFri, 14 Dec 2012 14:24:01 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/14/t1355513066km54l1ed19sgcxm.htm/, Retrieved Thu, 25 Apr 2024 19:27:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199724, Retrieved Thu, 25 Apr 2024 19:27:48 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

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] [] [2010-11-01 13:07:12] [b98453cac15ba1066b407e146608df68]
-   PD  [Paired and Unpaired Two Samples Tests about the Mean] [Paper] [2012-12-06 13:02:38] [9d44b52ac7f20a3e9be7c3c8470fe2cd]
- R PD      [Paired and Unpaired Two Samples Tests about the Mean] [paper] [2012-12-14 19:24:01] [0fc4686e0b584a6b9d6d9039dcebbcd5] [Current]
-    D        [Paired and Unpaired Two Samples Tests about the Mean] [paper] [2012-12-14 19:35:56] [e37f7a7b9ab1c2cdf6c8d8ef0222ab12]
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Dataset

Dataseries X:
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Boxplots 
26	NA	21	NA	21	NA	23	NA	17	NA	23	NA	4	NA	127	NA
20	NA	16	NA	15	NA	24	NA	17	NA	20	NA	4	NA	108	NA
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25	NA	24	NA	17	NA	23	NA	24	NA	14	NA	4	NA	123	NA
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NA	28	NA	28	NA	24	NA	28	NA	28	NA	27	NA	4	NA	159
22	NA	25	NA	15	NA	26	NA	23	NA	22	NA	4	NA	129	NA
18	NA	19	NA	15	NA	26	NA	21	NA	27	NA	7	NA	119	NA
23	NA	20	NA	10	NA	23	NA	21	NA	26	NA	4	NA	119	NA
20	NA	24	NA	14	NA	22	NA	26	NA	22	NA	6	NA	122	NA
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NA	26	NA	25	NA	12	NA	21	NA	21	NA	19	NA	4	NA	120
15	NA	12	NA	9	NA	20	NA	18	NA	24	NA	16	NA	82	NA
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NA	13	NA	14	NA	10	NA	20	NA	24	NA	28	NA	9	NA	100
18	NA	16	NA	17	NA	22	NA	15	NA	21	NA	9	NA	100	NA
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NA	24	NA	22	NA	19	NA	23	NA	24	NA	24	NA	4	NA	132
18	NA	20	NA	10	NA	22	NA	21	NA	21	NA	5	NA	107	NA
20	NA	19	NA	14	NA	24	NA	20	NA	21	NA	4	NA	114	NA
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24	NA	18	NA	9	NA	17	NA	20	NA	25	NA	4	NA	109	NA
18	NA	17	NA	12	NA	20	NA	22	NA	23	NA	6	NA	106	NA
21	NA	27	NA	16	NA	23	NA	20	NA	21	NA	4	NA	124	NA
NA	23	NA	25	NA	11	NA	23	NA	26	NA	16	NA	4	NA	120
17	NA	19	NA	18	NA	20	NA	18	NA	17	NA	18	NA	91	NA
NA	22	NA	22	NA	11	NA	28	NA	22	NA	25	NA	4	NA	126
NA	24	NA	24	NA	24	NA	24	NA	24	NA	24	NA	6	NA	138
NA	21	NA	20	NA	17	NA	24	NA	17	NA	23	NA	4	NA	118
22	NA	19	NA	18	NA	24	NA	24	NA	25	NA	4	NA	128	NA
16	NA	11	NA	9	NA	24	NA	20	NA	23	NA	5	NA	98	NA
21	NA	22	NA	19	NA	28	NA	19	NA	28	NA	4	NA	133	NA
NA	23	NA	22	NA	18	NA	25	NA	20	NA	26	NA	4	NA	130
NA	22	NA	16	NA	12	NA	21	NA	15	NA	22	NA	5	NA	103
24	NA	20	NA	23	NA	25	NA	23	NA	19	NA	10	NA	124	NA
24	NA	24	NA	22	NA	25	NA	26	NA	26	NA	5	NA	142	NA
16	NA	16	NA	14	NA	18	NA	22	NA	18	NA	8	NA	96	NA
16	NA	16	NA	14	NA	17	NA	20	NA	18	NA	8	NA	93	NA
NA	21	NA	22	NA	16	NA	26	NA	24	NA	25	NA	5	NA	129
NA	26	NA	24	NA	23	NA	28	NA	26	NA	27	NA	4	NA	150
NA	15	NA	16	NA	7	NA	21	NA	21	NA	12	NA	4	NA	88
NA	25	NA	27	NA	10	NA	27	NA	25	NA	15	NA	4	NA	125
18	NA	11	NA	12	NA	22	NA	13	NA	21	NA	5	NA	92	NA
NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20	NA	20	NA	12	NA	25	NA	22	NA	22	NA	4	NA	117	NA
NA	17	NA	20	NA	17	NA	22	NA	23	NA	21	NA	8	NA	112
NA	25	NA	27	NA	21	NA	23	NA	28	NA	24	NA	4	NA	144
24	NA	20	NA	16	NA	26	NA	22	NA	27	NA	5	NA	130	NA
17	NA	12	NA	11	NA	19	NA	20	NA	22	NA	14	NA	87	NA
19	NA	8	NA	14	NA	25	NA	6	NA	28	NA	8	NA	92	NA
20	NA	21	NA	13	NA	21	NA	21	NA	26	NA	8	NA	114	NA
15	NA	18	NA	9	NA	13	NA	20	NA	10	NA	4	NA	81	NA
NA	27	NA	24	NA	19	NA	24	NA	18	NA	19	NA	4	NA	127
22	NA	16	NA	13	NA	25	NA	23	NA	22	NA	6	NA	115	NA
23	NA	18	NA	19	NA	26	NA	20	NA	21	NA	4	NA	123	NA
16	NA	20	NA	13	NA	25	NA	24	NA	24	NA	7	NA	115	NA
19	NA	20	NA	13	NA	25	NA	22	NA	25	NA	7	NA	117	NA
NA	25	NA	19	NA	13	NA	22	NA	21	NA	21	NA	4	NA	117
19	NA	17	NA	14	NA	21	NA	18	NA	20	NA	6	NA	103	NA
NA	19	NA	16	NA	12	NA	23	NA	21	NA	21	NA	4	NA	108
NA	26	NA	26	NA	22	NA	25	NA	23	NA	24	NA	7	NA	139
21	NA	15	NA	11	NA	24	NA	23	NA	23	NA	4	NA	113	NA
NA	20	NA	22	NA	5	NA	21	NA	15	NA	18	NA	4	NA	97
24	NA	17	NA	18	NA	21	NA	21	NA	24	NA	8	NA	117	NA
22	NA	23	NA	19	NA	25	NA	24	NA	24	NA	4	NA	133	NA
NA	20	NA	21	NA	14	NA	22	NA	23	NA	19	NA	4	NA	115
18	NA	19	NA	15	NA	20	NA	21	NA	20	NA	10	NA	103	NA
NA	18	NA	14	NA	12	NA	20	NA	21	NA	18	NA	8	NA	95
24	NA	17	NA	19	NA	23	NA	20	NA	20	NA	6	NA	117	NA
24	NA	12	NA	15	NA	28	NA	11	NA	27	NA	4	NA	113	NA
22	NA	24	NA	17	NA	23	NA	22	NA	23	NA	4	NA	127	NA
23	NA	18	NA	8	NA	28	NA	27	NA	26	NA	4	NA	126	NA
22	NA	20	NA	10	NA	24	NA	25	NA	23	NA	5	NA	119	NA
20	NA	16	NA	12	NA	18	NA	18	NA	17	NA	4	NA	97	NA
18	NA	20	NA	12	NA	20	NA	20	NA	21	NA	6	NA	105	NA
25	NA	22	NA	20	NA	28	NA	24	NA	25	NA	4	NA	140	NA
NA	18	NA	12	NA	12	NA	21	NA	10	NA	23	NA	5	NA	91
16	NA	16	NA	12	NA	21	NA	27	NA	27	NA	7	NA	112	NA
20	NA	17	NA	14	NA	25	NA	21	NA	24	NA	8	NA	113	NA
NA	19	NA	22	NA	6	NA	19	NA	21	NA	20	NA	5	NA	102
15	NA	12	NA	10	NA	18	NA	18	NA	27	NA	8	NA	92	NA
19	NA	14	NA	18	NA	21	NA	15	NA	21	NA	10	NA	98	NA
19	NA	23	NA	18	NA	22	NA	24	NA	24	NA	8	NA	122	NA
16	NA	15	NA	7	NA	24	NA	22	NA	21	NA	5	NA	100	NA
17	NA	17	NA	18	NA	15	NA	14	NA	15	NA	12	NA	84	NA
28	NA	28	NA	9	NA	28	NA	28	NA	25	NA	4	NA	142	NA
NA	23	NA	20	NA	17	NA	26	NA	18	NA	25	NA	5	NA	124
25	NA	23	NA	22	NA	23	NA	26	NA	22	NA	4	NA	137	NA
20	NA	13	NA	11	NA	26	NA	17	NA	24	NA	6	NA	105	NA
NA	17	NA	18	NA	15	NA	20	NA	19	NA	21	NA	4	NA	106
NA	23	NA	23	NA	17	NA	22	NA	22	NA	22	NA	4	NA	125
16	NA	19	NA	15	NA	20	NA	18	NA	23	NA	7	NA	104	NA
NA	23	NA	23	NA	22	NA	23	NA	24	NA	22	NA	7	NA	130
NA	11	NA	12	NA	9	NA	22	NA	15	NA	20	NA	10	NA	79
NA	18	NA	16	NA	13	NA	24	NA	18	NA	23	NA	4	NA	108
NA	24	NA	23	NA	20	NA	23	NA	26	NA	25	NA	5	NA	136
23	NA	13	NA	14	NA	22	NA	11	NA	23	NA	8	NA	98	NA
21	NA	22	NA	14	NA	26	NA	26	NA	22	NA	11	NA	120	NA
NA	16	NA	18	NA	12	NA	23	NA	21	NA	25	NA	7	NA	108
NA	24	NA	23	NA	20	NA	27	NA	23	NA	26	NA	4	NA	139
23	NA	20	NA	20	NA	23	NA	23	NA	22	NA	8	NA	123	NA
18	NA	10	NA	8	NA	21	NA	15	NA	24	NA	6	NA	90	NA
20	NA	17	NA	17	NA	26	NA	22	NA	24	NA	7	NA	119	NA
9	NA	18	NA	9	NA	23	NA	26	NA	25	NA	5	NA	105	NA
NA	24	NA	15	NA	18	NA	21	NA	16	NA	20	NA	4	NA	110
25	NA	23	NA	22	NA	27	NA	20	NA	26	NA	8	NA	135	NA
20	NA	17	NA	10	NA	19	NA	18	NA	21	NA	4	NA	101	NA
NA	21	NA	17	NA	13	NA	23	NA	22	NA	26	NA	8	NA	114
NA	25	NA	22	NA	15	NA	25	NA	16	NA	21	NA	6	NA	118
NA	22	NA	20	NA	18	NA	23	NA	19	NA	22	NA	4	NA	120
NA	21	NA	20	NA	18	NA	22	NA	20	NA	16	NA	9	NA	108
21	NA	19	NA	12	NA	22	NA	19	NA	26	NA	5	NA	114	NA
22	NA	18	NA	12	NA	25	NA	23	NA	28	NA	6	NA	122	NA
27	NA	22	NA	20	NA	25	NA	24	NA	18	NA	4	NA	132	NA
NA	24	NA	20	NA	12	NA	28	NA	25	NA	25	NA	4	NA	130
NA	24	NA	22	NA	16	NA	28	NA	21	NA	23	NA	4	NA	130
NA	21	NA	18	NA	16	NA	20	NA	21	NA	21	NA	5	NA	112
18	NA	16	NA	18	NA	25	NA	23	NA	20	NA	6	NA	114	NA
16	NA	16	NA	16	NA	19	NA	27	NA	25	NA	16	NA	103	NA
22	NA	16	NA	13	NA	25	NA	23	NA	22	NA	6	NA	115	NA
20	NA	16	NA	17	NA	22	NA	18	NA	21	NA	6	NA	108	NA
NA	18	NA	17	NA	13	NA	18	NA	16	NA	16	NA	4	NA	94
20	NA	18	NA	17	NA	20	NA	16	NA	18	NA	4	NA	105	NA

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 5 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199724&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199724&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199724&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 time5 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 120.2857142857143
Mean of Sample 221.1587301587302
t-stat-1.48110480618626
df159
p-value0.140557605259178
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.03714891457418,0.291117168542431]
F-test to compare two variances
F-stat0.945582301473422
df97
p-value0.794909638674922
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.593534272843385,1.47225280127374]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 20.2857142857143 \tabularnewline
Mean of Sample 2 & 21.1587301587302 \tabularnewline
t-stat & -1.48110480618626 \tabularnewline
df & 159 \tabularnewline
p-value & 0.140557605259178 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-2.03714891457418,0.291117168542431] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.945582301473422 \tabularnewline
df & 97 \tabularnewline
p-value & 0.794909638674922 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.593534272843385,1.47225280127374] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199724&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]20.2857142857143[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]21.1587301587302[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.48110480618626[/C][/ROW]
[ROW][C]df[/C][C]159[/C][/ROW]
[ROW][C]p-value[/C][C]0.140557605259178[/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][-2.03714891457418,0.291117168542431][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.945582301473422[/C][/ROW]
[ROW][C]df[/C][C]97[/C][/ROW]
[ROW][C]p-value[/C][C]0.794909638674922[/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][0.593534272843385,1.47225280127374][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199724&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199724&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 120.2857142857143
Mean of Sample 221.1587301587302
t-stat-1.48110480618626
df159
p-value0.140557605259178
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.03714891457418,0.291117168542431]
F-test to compare two variances
F-stat0.945582301473422
df97
p-value0.794909638674922
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.593534272843385,1.47225280127374]






Welch Two Sample t-test (unpaired)
Mean of Sample 120.2857142857143
Mean of Sample 221.1587301587302
t-stat-1.47206965608054
df129.662184007628
p-value0.143425153351939
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.04632976094352,0.300298014911777]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 20.2857142857143 \tabularnewline
Mean of Sample 2 & 21.1587301587302 \tabularnewline
t-stat & -1.47206965608054 \tabularnewline
df & 129.662184007628 \tabularnewline
p-value & 0.143425153351939 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-2.04632976094352,0.300298014911777] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199724&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]20.2857142857143[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]21.1587301587302[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.47206965608054[/C][/ROW]
[ROW][C]df[/C][C]129.662184007628[/C][/ROW]
[ROW][C]p-value[/C][C]0.143425153351939[/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][-2.04632976094352,0.300298014911777][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199724&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199724&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 120.2857142857143
Mean of Sample 221.1587301587302
t-stat-1.47206965608054
df129.662184007628
p-value0.143425153351939
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.04632976094352,0.300298014911777]






Wicoxon rank sum test with continuity correction (unpaired)
W2609.5
p-value0.0971999424750079
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.147392290249433
p-value0.375392259601847
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.147392290249433
p-value0.375392259601847

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 2609.5 \tabularnewline
p-value & 0.0971999424750079 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.147392290249433 \tabularnewline
p-value & 0.375392259601847 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.147392290249433 \tabularnewline
p-value & 0.375392259601847 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199724&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]2609.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.0971999424750079[/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]0.147392290249433[/C][/ROW]
[ROW][C]p-value[/C][C]0.375392259601847[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.147392290249433[/C][/ROW]
[ROW][C]p-value[/C][C]0.375392259601847[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199724&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199724&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)
W2609.5
p-value0.0971999424750079
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.147392290249433
p-value0.375392259601847
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.147392290249433
p-value0.375392259601847


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):
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')