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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_chi_squared_tests.wasp
Title produced by softwareChi-Squared Test, McNemar Test, and Fisher Exact Test
Date of computationFri, 16 Jan 2015 09:07:48 +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/2015/Jan/16/t1421399330xpgl5fuwukv1ec8.htm/, Retrieved Wed, 15 May 2024 09:26:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=273521, Retrieved Wed, 15 May 2024 09:26:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact47
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [vraag2 ] [2015-01-16 09:07:48] [cf0ec5d34597f312b7dfbfe84499cd1d] [Current]
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Dataseries X:
4.2 "'VC'" 0.5
11.5 "'VC'" 0.5
7.3 "'VC'" 0.5
5.8 "'VC'" 0.5
6.4 "'VC'" 0.5
10 "'VC'" 0.5
11.2 "'VC'" 0.5
11.2 "'VC'" 0.5
5.2 "'VC'" 0.5
7 "'VC'" 0.5
16.5 "'VC'" 1
16.5 "'VC'" 1
15.2 "'VC'" 1
17.3 "'VC'" 1
22.5 "'VC'" 1
17.3 "'VC'" 1
13.6 "'VC'" 1
14.5 "'VC'" 1
18.8 "'VC'" 1
15.5 "'VC'" 1
23.6 "'VC'" 2
18.5 "'VC'" 2
33.9 "'VC'" 2
25.5 "'VC'" 2
26.4 "'VC'" 2
32.5 "'VC'" 2
26.7 "'VC'" 2
21.5 "'VC'" 2
23.3 "'VC'" 2
29.5 "'VC'" 2
15.2 "'OJ'" 0.5
21.5 "'OJ'" 0.5
17.6 "'OJ'" 0.5
9.7 "'OJ'" 0.5
14.5 "'OJ'" 0.5
10 "'OJ'" 0.5
8.2 "'OJ'" 0.5
9.4 "'OJ'" 0.5
16.5 "'OJ'" 0.5
9.7 "'OJ'" 0.5
19.7 "'OJ'" 1
23.3 "'OJ'" 1
23.6 "'OJ'" 1
26.4 "'OJ'" 1
20 "'OJ'" 1
25.2 "'OJ'" 1
25.8 "'OJ'" 1
21.2 "'OJ'" 1
14.5 "'OJ'" 1
27.3 "'OJ'" 1
25.5 "'OJ'" 2
26.4 "'OJ'" 2
22.4 "'OJ'" 2
24.5 "'OJ'" 2
24.8 "'OJ'" 2
30.9 "'OJ'" 2
26.4 "'OJ'" 2
27.3 "'OJ'" 2
29.4 "'OJ'" 2
23 "'OJ'" 2




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=273521&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=273521&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=273521&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Tabulation of Results
Spiergroei x Dosis
0.512
10200
11.2200
11.5100
13.6010
14.5120
15.2110
15.5010
16.5120
17.3020
17.6100
18.5001
18.8010
19.7010
20010
21.2010
21.5101
22.4001
22.5010
23001
23.3011
23.6011
24.5001
24.8001
25.2010
25.5002
25.8010
26.4013
26.7001
27.3011
29.4001
29.5001
30.9001
32.5001
33.9001
4.2100
5.2100
5.8100
6.4100
7100
7.3100
8.2100
9.4100
9.7200

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Spiergroei  x  Dosis \tabularnewline
  & 0.5 & 1 & 2 \tabularnewline
10 & 2 & 0 & 0 \tabularnewline
11.2 & 2 & 0 & 0 \tabularnewline
11.5 & 1 & 0 & 0 \tabularnewline
13.6 & 0 & 1 & 0 \tabularnewline
14.5 & 1 & 2 & 0 \tabularnewline
15.2 & 1 & 1 & 0 \tabularnewline
15.5 & 0 & 1 & 0 \tabularnewline
16.5 & 1 & 2 & 0 \tabularnewline
17.3 & 0 & 2 & 0 \tabularnewline
17.6 & 1 & 0 & 0 \tabularnewline
18.5 & 0 & 0 & 1 \tabularnewline
18.8 & 0 & 1 & 0 \tabularnewline
19.7 & 0 & 1 & 0 \tabularnewline
20 & 0 & 1 & 0 \tabularnewline
21.2 & 0 & 1 & 0 \tabularnewline
21.5 & 1 & 0 & 1 \tabularnewline
22.4 & 0 & 0 & 1 \tabularnewline
22.5 & 0 & 1 & 0 \tabularnewline
23 & 0 & 0 & 1 \tabularnewline
23.3 & 0 & 1 & 1 \tabularnewline
23.6 & 0 & 1 & 1 \tabularnewline
24.5 & 0 & 0 & 1 \tabularnewline
24.8 & 0 & 0 & 1 \tabularnewline
25.2 & 0 & 1 & 0 \tabularnewline
25.5 & 0 & 0 & 2 \tabularnewline
25.8 & 0 & 1 & 0 \tabularnewline
26.4 & 0 & 1 & 3 \tabularnewline
26.7 & 0 & 0 & 1 \tabularnewline
27.3 & 0 & 1 & 1 \tabularnewline
29.4 & 0 & 0 & 1 \tabularnewline
29.5 & 0 & 0 & 1 \tabularnewline
30.9 & 0 & 0 & 1 \tabularnewline
32.5 & 0 & 0 & 1 \tabularnewline
33.9 & 0 & 0 & 1 \tabularnewline
4.2 & 1 & 0 & 0 \tabularnewline
5.2 & 1 & 0 & 0 \tabularnewline
5.8 & 1 & 0 & 0 \tabularnewline
6.4 & 1 & 0 & 0 \tabularnewline
7 & 1 & 0 & 0 \tabularnewline
7.3 & 1 & 0 & 0 \tabularnewline
8.2 & 1 & 0 & 0 \tabularnewline
9.4 & 1 & 0 & 0 \tabularnewline
9.7 & 2 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=273521&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Spiergroei  x  Dosis[/C][/ROW]
[ROW][C] [/C][C]0.5[/C][C]1[/C][C]2[/C][/ROW]
[C]10[/C][C]2[/C][C]0[/C][C]0[/C][/ROW]
[C]11.2[/C][C]2[/C][C]0[/C][C]0[/C][/ROW]
[C]11.5[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]13.6[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]14.5[/C][C]1[/C][C]2[/C][C]0[/C][/ROW]
[C]15.2[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[C]15.5[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]16.5[/C][C]1[/C][C]2[/C][C]0[/C][/ROW]
[C]17.3[/C][C]0[/C][C]2[/C][C]0[/C][/ROW]
[C]17.6[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]18.5[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]18.8[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]19.7[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]20[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]21.2[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]21.5[/C][C]1[/C][C]0[/C][C]1[/C][/ROW]
[C]22.4[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]22.5[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]23[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]23.3[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[C]23.6[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[C]24.5[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]24.8[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]25.2[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]25.5[/C][C]0[/C][C]0[/C][C]2[/C][/ROW]
[C]25.8[/C][C]0[/C][C]1[/C][C]0[/C][/ROW]
[C]26.4[/C][C]0[/C][C]1[/C][C]3[/C][/ROW]
[C]26.7[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]27.3[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[C]29.4[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]29.5[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]30.9[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]32.5[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]33.9[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[C]4.2[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]5.2[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]5.8[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]6.4[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]7[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]7.3[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]8.2[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]9.4[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[C]9.7[/C][C]2[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=273521&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=273521&T=1

As an alternative you can also use a QR Code:  

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

Tabulation of Results
Spiergroei x Dosis
0.512
10200
11.2200
11.5100
13.6010
14.5120
15.2110
15.5010
16.5120
17.3020
17.6100
18.5001
18.8010
19.7010
20010
21.2010
21.5101
22.4001
22.5010
23001
23.3011
23.6011
24.5001
24.8001
25.2010
25.5002
25.8010
26.4013
26.7001
27.3011
29.4001
29.5001
30.9001
32.5001
33.9001
4.2100
5.2100
5.8100
6.4100
7100
7.3100
8.2100
9.4100
9.7200







Tabulation of Expected Results
Spiergroei x Dosis
0.512
100.670.670.67
11.20.670.670.67
11.50.330.330.33
13.60.330.330.33
14.5111
15.20.670.670.67
15.50.330.330.33
16.5111
17.30.670.670.67
17.60.330.330.33
18.50.330.330.33
18.80.330.330.33
19.70.330.330.33
200.330.330.33
21.20.330.330.33
21.50.670.670.67
22.40.330.330.33
22.50.330.330.33
230.330.330.33
23.30.670.670.67
23.60.670.670.67
24.50.330.330.33
24.80.330.330.33
25.20.330.330.33
25.50.670.670.67
25.80.330.330.33
26.41.331.331.33
26.70.330.330.33
27.30.670.670.67
29.40.330.330.33
29.50.330.330.33
30.90.330.330.33
32.50.330.330.33
33.90.330.330.33
4.20.330.330.33
5.20.330.330.33
5.80.330.330.33
6.40.330.330.33
70.330.330.33
7.30.330.330.33
8.20.330.330.33
9.40.330.330.33
9.70.670.670.67

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Spiergroei  x  Dosis \tabularnewline
  & 0.5 & 1 & 2 \tabularnewline
10 & 0.67 & 0.67 & 0.67 \tabularnewline
11.2 & 0.67 & 0.67 & 0.67 \tabularnewline
11.5 & 0.33 & 0.33 & 0.33 \tabularnewline
13.6 & 0.33 & 0.33 & 0.33 \tabularnewline
14.5 & 1 & 1 & 1 \tabularnewline
15.2 & 0.67 & 0.67 & 0.67 \tabularnewline
15.5 & 0.33 & 0.33 & 0.33 \tabularnewline
16.5 & 1 & 1 & 1 \tabularnewline
17.3 & 0.67 & 0.67 & 0.67 \tabularnewline
17.6 & 0.33 & 0.33 & 0.33 \tabularnewline
18.5 & 0.33 & 0.33 & 0.33 \tabularnewline
18.8 & 0.33 & 0.33 & 0.33 \tabularnewline
19.7 & 0.33 & 0.33 & 0.33 \tabularnewline
20 & 0.33 & 0.33 & 0.33 \tabularnewline
21.2 & 0.33 & 0.33 & 0.33 \tabularnewline
21.5 & 0.67 & 0.67 & 0.67 \tabularnewline
22.4 & 0.33 & 0.33 & 0.33 \tabularnewline
22.5 & 0.33 & 0.33 & 0.33 \tabularnewline
23 & 0.33 & 0.33 & 0.33 \tabularnewline
23.3 & 0.67 & 0.67 & 0.67 \tabularnewline
23.6 & 0.67 & 0.67 & 0.67 \tabularnewline
24.5 & 0.33 & 0.33 & 0.33 \tabularnewline
24.8 & 0.33 & 0.33 & 0.33 \tabularnewline
25.2 & 0.33 & 0.33 & 0.33 \tabularnewline
25.5 & 0.67 & 0.67 & 0.67 \tabularnewline
25.8 & 0.33 & 0.33 & 0.33 \tabularnewline
26.4 & 1.33 & 1.33 & 1.33 \tabularnewline
26.7 & 0.33 & 0.33 & 0.33 \tabularnewline
27.3 & 0.67 & 0.67 & 0.67 \tabularnewline
29.4 & 0.33 & 0.33 & 0.33 \tabularnewline
29.5 & 0.33 & 0.33 & 0.33 \tabularnewline
30.9 & 0.33 & 0.33 & 0.33 \tabularnewline
32.5 & 0.33 & 0.33 & 0.33 \tabularnewline
33.9 & 0.33 & 0.33 & 0.33 \tabularnewline
4.2 & 0.33 & 0.33 & 0.33 \tabularnewline
5.2 & 0.33 & 0.33 & 0.33 \tabularnewline
5.8 & 0.33 & 0.33 & 0.33 \tabularnewline
6.4 & 0.33 & 0.33 & 0.33 \tabularnewline
7 & 0.33 & 0.33 & 0.33 \tabularnewline
7.3 & 0.33 & 0.33 & 0.33 \tabularnewline
8.2 & 0.33 & 0.33 & 0.33 \tabularnewline
9.4 & 0.33 & 0.33 & 0.33 \tabularnewline
9.7 & 0.67 & 0.67 & 0.67 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=273521&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Spiergroei  x  Dosis[/C][/ROW]
[ROW][C] [/C][C]0.5[/C][C]1[/C][C]2[/C][/ROW]
[C]10[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]11.2[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]11.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]13.6[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]14.5[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[C]15.2[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]15.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]16.5[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[C]17.3[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]17.6[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]18.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]18.8[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]19.7[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]20[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]21.2[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]21.5[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]22.4[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]22.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]23[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]23.3[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]23.6[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]24.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]24.8[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]25.2[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]25.5[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]25.8[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]26.4[/C][C]1.33[/C][C]1.33[/C][C]1.33[/C][/ROW]
[C]26.7[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]27.3[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[C]29.4[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]29.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]30.9[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]32.5[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]33.9[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]4.2[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]5.2[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]5.8[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]6.4[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]7[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]7.3[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]8.2[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]9.4[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[C]9.7[/C][C]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=273521&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=273521&T=2

As an alternative you can also use a QR Code:  

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

Tabulation of Expected Results
Spiergroei x Dosis
0.512
100.670.670.67
11.20.670.670.67
11.50.330.330.33
13.60.330.330.33
14.5111
15.20.670.670.67
15.50.330.330.33
16.5111
17.30.670.670.67
17.60.330.330.33
18.50.330.330.33
18.80.330.330.33
19.70.330.330.33
200.330.330.33
21.20.330.330.33
21.50.670.670.67
22.40.330.330.33
22.50.330.330.33
230.330.330.33
23.30.670.670.67
23.60.670.670.67
24.50.330.330.33
24.80.330.330.33
25.20.330.330.33
25.50.670.670.67
25.80.330.330.33
26.41.331.331.33
26.70.330.330.33
27.30.670.670.67
29.40.330.330.33
29.50.330.330.33
30.90.330.330.33
32.50.330.330.33
33.90.330.330.33
4.20.330.330.33
5.20.330.330.33
5.80.330.330.33
6.40.330.330.33
70.330.330.33
7.30.330.330.33
8.20.330.330.33
9.40.330.330.33
9.70.670.670.67







Statistical Results
Pearson's Chi-squared test
Pearson Chi Square Statistic92.5
Degrees of Freedom84
P value0.25

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Pearson Chi Square Statistic & 92.5 \tabularnewline
Degrees of Freedom & 84 \tabularnewline
P value & 0.25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=273521&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test[/C][/ROW]
[ROW][C]Pearson Chi Square Statistic[/C][C]92.5[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]84[/C][/ROW]
[ROW][C]P value[/C][C]0.25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=273521&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=273521&T=3

As an alternative you can also use a QR Code:  

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

Statistical Results
Pearson's Chi-squared test
Pearson Chi Square Statistic92.5
Degrees of Freedom84
P value0.25



Parameters (Session):
par1 = 1 ; par2 = 3 ; par3 = Pearson Chi-Squared ;
Parameters (R input):
par1 = 1 ; par2 = 3 ; par3 = Pearson Chi-Squared ;
R code (references can be found in the software module):
par3 <- 'Pearson Chi-Squared'
par2 <- '2'
par1 <- '1'
library(vcd)
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
simulate.p.value=FALSE
if (par3 == 'Exact Pearson Chi-Squared by Simulation') simulate.p.value=TRUE
x <- t(x)
(z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,]))))
(table1 <- table(z[,cat1],z[,cat2]))
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
bitmap(file='pic1.png')
assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, table1[nr, nc], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
(cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )
if (par3 == 'McNemar Chi-Squared') {
(cst <- mcnemar.test(table1))
}
if (par3=='Fisher Exact Test') {
(cst <- fisher.test(table1))
}
if ((par3 != 'McNemar Chi-Squared') & (par3 != 'Fisher Exact Test')) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Statistical Results',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, cst$method, 2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
if (par3=='Pearson Chi-Squared') a<-table.element(a, 'Pearson Chi Square Statistic', 1, TRUE)
if (par3=='Exact Pearson Chi-Squared by Simulation') a<-table.element(a, 'Exact Pearson Chi Square Statistic', 1, TRUE)
if (par3=='McNemar Chi-Squared') a<-table.element(a, 'McNemar Chi Square Statistic', 1, TRUE)
if (par3=='Fisher Exact Test') a<-table.element(a, 'Odds Ratio', 1, TRUE)
if (par3=='Fisher Exact Test') {
if ((ncol(table1) == 2) & (nrow(table1) == 2)) {
a<-table.element(a, round(cst$estimate, digits=2), 1,FALSE)
} else {
a<-table.element(a, '--', 1,FALSE)
}
} else {
a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
}
a<-table.row.end(a)
if(!simulate.p.value){
if(par3!='Fisher Exact Test') {
a<-table.row.start(a)
a<-table.element(a, 'Degrees of Freedom', 1, TRUE)
a<-table.element(a, cst$parameter, 1,FALSE)
a<-table.row.end(a)
}
}
a<-table.row.start(a)
a<-table.element(a, 'P value', 1, TRUE)
a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')