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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationSun, 30 Dec 2018 14:25:15 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Dec/30/t154617632122nxjy37b7raix8.htm/, Retrieved Wed, 08 May 2024 06:28:45 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Wed, 08 May 2024 06:28:45 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10 10 10 10 21 36
8 8 9 15 22 32
8 6 12 14 17 33
9 10 14 14 21 39
5 8 6 8 19 34
10 10 13 19 23 39
8 7 12 17 21 36
9 10 13 18 22 33
8 6 6 10 11 30
7 7 12 15 20 39
10 9 10 16 18 37
10 6 9 12 16 37
9 7 12 13 18 35
4 6 7 10 13 32
4 4 10 14 17 36
8 6 11 15 20 36
9 8 15 20 20 41
10 9 10 9 15 36
8 8 12 12 18 37
5 6 10 13 15 29
10 6 12 16 19 39
8 10 11 12 19 37
7 8 11 14 19 32
8 8 12 15 20 36
8 7 15 19 20 43
9 4 12 16 16 30
8 9 11 16 18 33
6 8 9 14 17 28
8 10 11 14 18 30
8 8 11 14 13 28
5 6 9 13 20 39
9 7 15 18 21 34
8 8 12 15 17 34
8 5 9 15 19 29
8 10 12 15 20 32
6 2 12 13 15 33
6 6 9 14 15 27
9 7 9 15 19 35
8 5 11 14 18 38
9 8 12 19 22 40
10 7 12 16 20 34
8 7 12 16 18 34
8 10 12 12 14 26
7 7 6 10 15 39
7 6 11 11 17 34
10 10 12 13 16 39
8 6 9 14 17 26
7 5 11 11 15 30
10 8 9 11 17 34
7 8 10 16 18 34
7 5 10 9 16 29
9 8 9 16 18 41
9 10 12 19 22 43
8 7 11 13 16 31
6 7 9 15 16 33
8 7 9 14 20 34
9 7 12 15 18 30
2 2 6 11 16 23
6 4 10 14 16 29
8 6 12 15 20 35
8 7 11 17 21 40
7 9 14 16 18 27
8 9 8 13 15 30
6 4 9 15 18 27
10 9 10 14 18 29
10 9 10 15 20 33
10 8 10 14 18 32
8 7 11 12 16 33
8 9 10 12 19 36
7 7 12 15 20 34
10 6 14 17 22 45
5 7 10 13 18 30
3 2 8 5 8 22
2 3 8 7 13 24
3 4 7 10 13 25
4 5 11 15 18 26
2 2 6 9 12 27
6 6 9 9 16 27
8 8 12 15 21 35
8 5 12 14 20 36
5 4 12 11 18 32
10 10 9 18 22 35
9 10 15 20 23 35
8 10 15 20 23 36
9 9 13 16 21 37
8 5 9 15 16 33
5 5 12 14 14 25
7 7 9 13 18 35
9 10 15 18 22 37
8 9 11 14 20 36
4 8 11 12 18 35
7 8 6 9 12 29
8 8 14 19 17 35
7 8 11 13 15 31
7 8 8 12 18 30
9 7 10 14 18 37
6 6 10 6 15 36
7 8 9 14 16 35
4 2 8 11 15 32
6 5 9 11 16 34
10 4 10 14 19 37
9 9 11 12 19 36
10 10 14 19 23 39
8 6 12 13 20 37
4 4 9 14 18 31
8 10 13 17 21 40
5 6 8 12 19 38
8 7 12 16 18 35
9 7 14 15 19 38
8 8 9 15 17 32
4 6 10 15 21 41
8 5 12 16 19 28
10 6 12 15 24 40
6 7 9 12 12 25
7 6 9 13 15 28
10 9 12 14 18 37
9 9 15 17 19 37
8 7 12 14 22 40
3 6 11 14 19 26
8 7 8 14 16 30
7 7 11 15 19 32
7 8 11 11 18 31
8 7 10 11 18 28
8 8 12 16 19 34
7 7 9 12 21 39
7 4 11 12 19 33
9 10 15 19 22 43
9 8 14 18 23 37
9 8 6 16 17 31
4 2 9 16 18 31
6 6 9 13 19 34
6 4 8 11 15 32
6 4 7 10 14 27
8 9 10 14 18 34
3 2 6 14 17 28
8 6 9 14 19 32
8 7 9 16 16 39
6 4 7 10 14 28
10 10 11 16 20 39
2 3 9 7 16 32
9 7 12 16 18 36
6 4 9 15 16 31
6 8 10 17 21 39
5 4 11 11 16 23
4 5 7 11 14 25
7 6 12 10 16 32
5 5 8 13 19 32
8 9 13 14 19 36
6 6 11 13 19 39
9 8 11 13 18 31
6 4 12 12 16 32
4 4 11 10 14 28
7 8 12 15 19 34
2 4 3 6 11 28
8 10 10 15 18 38
9 8 13 15 18 35
6 5 10 11 16 32
5 3 6 14 20 26
7 7 11 14 18 32
8 6 12 16 20 28
4 5 9 12 16 31
9 5 10 15 18 33
9 9 15 20 19 38
9 2 9 12 19 38
7 7 6 9 15 36
5 7 9 13 17 31
7 5 15 15 21 36
9 9 15 19 24 43
8 4 9 11 16 37
6 5 11 11 13 28
9 9 9 17 21 35
8 7 11 15 16 34
7 6 10 14 17 40
7 8 9 15 17 31
7 7 6 11 18 41
8 6 12 12 18 35
10 8 13 15 23 38
6 6 12 16 20 37
6 7 12 16 20 31

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time5 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]5 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
Intention_to_Use ~ Relative_Advantage
means8.947-4.822-5.947-3.225-2.477-1.982-1.29-1.166-0.114

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Intention_to_Use  ~  Relative_Advantage \tabularnewline
means & 8.947 & -4.822 & -5.947 & -3.225 & -2.477 & -1.982 & -1.29 & -1.166 & -0.114 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Intention_to_Use  ~  Relative_Advantage[/C][/ROW]
[ROW][C]means[/C][C]8.947[/C][C]-4.822[/C][C]-5.947[/C][C]-3.225[/C][C]-2.477[/C][C]-1.982[/C][C]-1.29[/C][C]-1.166[/C][C]-0.114[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

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

ANOVA Model
Intention_to_Use ~ Relative_Advantage
means8.947-4.822-5.947-3.225-2.477-1.982-1.29-1.166-0.114






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Relative_Advantage8301.54537.69316.6660
Residuals170384.4892.262 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Relative_Advantage & 8 & 301.545 & 37.693 & 16.666 & 0 \tabularnewline
Residuals & 170 & 384.489 & 2.262 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Relative_Advantage[/C][C]8[/C][C]301.545[/C][C]37.693[/C][C]16.666[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]170[/C][C]384.489[/C][C]2.262[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Relative_Advantage8301.54537.69316.6660
Residuals170384.4892.262






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10-4.822-6.814-2.8310
3-10-5.947-8.883-3.0120
4-10-3.225-4.779-1.6710
5-10-2.477-4.054-0.8990
6-10-1.982-3.377-0.5870
7-10-1.29-2.6370.0560.072
8-10-1.166-2.5350.2030.164
9-10-0.114-1.6681.441
3-2-1.125-4.3242.0740.973
4-21.597-0.4113.6050.24
5-22.3460.324.3720.011
6-22.8410.9534.7280
7-23.5321.685.3840
8-23.6561.7885.5240
9-24.7082.76.7160
4-32.722-0.2255.6690.095
5-33.4710.5116.430.009
6-33.9661.16.8310.001
7-34.6571.8147.50
8-34.7811.9287.6350
9-35.8332.8868.780
5-40.748-0.852.3470.867
6-41.243-0.1752.6610.137
7-41.9350.5643.3060.001
8-42.0590.6673.4510
9-43.1111.5364.6860
6-50.495-0.9491.9380.977
7-51.187-0.212.5840.167
8-51.311-0.1082.7290.095
9-52.3630.7653.9610
7-60.692-0.4951.8780.661
8-60.816-0.3962.0270.466
9-61.8680.453.2860.002
8-70.124-1.0321.281
9-71.176-0.1942.5470.157
9-81.052-0.342.4440.305

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-10 & -4.822 & -6.814 & -2.831 & 0 \tabularnewline
3-10 & -5.947 & -8.883 & -3.012 & 0 \tabularnewline
4-10 & -3.225 & -4.779 & -1.671 & 0 \tabularnewline
5-10 & -2.477 & -4.054 & -0.899 & 0 \tabularnewline
6-10 & -1.982 & -3.377 & -0.587 & 0 \tabularnewline
7-10 & -1.29 & -2.637 & 0.056 & 0.072 \tabularnewline
8-10 & -1.166 & -2.535 & 0.203 & 0.164 \tabularnewline
9-10 & -0.114 & -1.668 & 1.44 & 1 \tabularnewline
3-2 & -1.125 & -4.324 & 2.074 & 0.973 \tabularnewline
4-2 & 1.597 & -0.411 & 3.605 & 0.24 \tabularnewline
5-2 & 2.346 & 0.32 & 4.372 & 0.011 \tabularnewline
6-2 & 2.841 & 0.953 & 4.728 & 0 \tabularnewline
7-2 & 3.532 & 1.68 & 5.384 & 0 \tabularnewline
8-2 & 3.656 & 1.788 & 5.524 & 0 \tabularnewline
9-2 & 4.708 & 2.7 & 6.716 & 0 \tabularnewline
4-3 & 2.722 & -0.225 & 5.669 & 0.095 \tabularnewline
5-3 & 3.471 & 0.511 & 6.43 & 0.009 \tabularnewline
6-3 & 3.966 & 1.1 & 6.831 & 0.001 \tabularnewline
7-3 & 4.657 & 1.814 & 7.5 & 0 \tabularnewline
8-3 & 4.781 & 1.928 & 7.635 & 0 \tabularnewline
9-3 & 5.833 & 2.886 & 8.78 & 0 \tabularnewline
5-4 & 0.748 & -0.85 & 2.347 & 0.867 \tabularnewline
6-4 & 1.243 & -0.175 & 2.661 & 0.137 \tabularnewline
7-4 & 1.935 & 0.564 & 3.306 & 0.001 \tabularnewline
8-4 & 2.059 & 0.667 & 3.451 & 0 \tabularnewline
9-4 & 3.111 & 1.536 & 4.686 & 0 \tabularnewline
6-5 & 0.495 & -0.949 & 1.938 & 0.977 \tabularnewline
7-5 & 1.187 & -0.21 & 2.584 & 0.167 \tabularnewline
8-5 & 1.311 & -0.108 & 2.729 & 0.095 \tabularnewline
9-5 & 2.363 & 0.765 & 3.961 & 0 \tabularnewline
7-6 & 0.692 & -0.495 & 1.878 & 0.661 \tabularnewline
8-6 & 0.816 & -0.396 & 2.027 & 0.466 \tabularnewline
9-6 & 1.868 & 0.45 & 3.286 & 0.002 \tabularnewline
8-7 & 0.124 & -1.032 & 1.28 & 1 \tabularnewline
9-7 & 1.176 & -0.194 & 2.547 & 0.157 \tabularnewline
9-8 & 1.052 & -0.34 & 2.444 & 0.305 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]2-10[/C][C]-4.822[/C][C]-6.814[/C][C]-2.831[/C][C]0[/C][/ROW]
[ROW][C]3-10[/C][C]-5.947[/C][C]-8.883[/C][C]-3.012[/C][C]0[/C][/ROW]
[ROW][C]4-10[/C][C]-3.225[/C][C]-4.779[/C][C]-1.671[/C][C]0[/C][/ROW]
[ROW][C]5-10[/C][C]-2.477[/C][C]-4.054[/C][C]-0.899[/C][C]0[/C][/ROW]
[ROW][C]6-10[/C][C]-1.982[/C][C]-3.377[/C][C]-0.587[/C][C]0[/C][/ROW]
[ROW][C]7-10[/C][C]-1.29[/C][C]-2.637[/C][C]0.056[/C][C]0.072[/C][/ROW]
[ROW][C]8-10[/C][C]-1.166[/C][C]-2.535[/C][C]0.203[/C][C]0.164[/C][/ROW]
[ROW][C]9-10[/C][C]-0.114[/C][C]-1.668[/C][C]1.44[/C][C]1[/C][/ROW]
[ROW][C]3-2[/C][C]-1.125[/C][C]-4.324[/C][C]2.074[/C][C]0.973[/C][/ROW]
[ROW][C]4-2[/C][C]1.597[/C][C]-0.411[/C][C]3.605[/C][C]0.24[/C][/ROW]
[ROW][C]5-2[/C][C]2.346[/C][C]0.32[/C][C]4.372[/C][C]0.011[/C][/ROW]
[ROW][C]6-2[/C][C]2.841[/C][C]0.953[/C][C]4.728[/C][C]0[/C][/ROW]
[ROW][C]7-2[/C][C]3.532[/C][C]1.68[/C][C]5.384[/C][C]0[/C][/ROW]
[ROW][C]8-2[/C][C]3.656[/C][C]1.788[/C][C]5.524[/C][C]0[/C][/ROW]
[ROW][C]9-2[/C][C]4.708[/C][C]2.7[/C][C]6.716[/C][C]0[/C][/ROW]
[ROW][C]4-3[/C][C]2.722[/C][C]-0.225[/C][C]5.669[/C][C]0.095[/C][/ROW]
[ROW][C]5-3[/C][C]3.471[/C][C]0.511[/C][C]6.43[/C][C]0.009[/C][/ROW]
[ROW][C]6-3[/C][C]3.966[/C][C]1.1[/C][C]6.831[/C][C]0.001[/C][/ROW]
[ROW][C]7-3[/C][C]4.657[/C][C]1.814[/C][C]7.5[/C][C]0[/C][/ROW]
[ROW][C]8-3[/C][C]4.781[/C][C]1.928[/C][C]7.635[/C][C]0[/C][/ROW]
[ROW][C]9-3[/C][C]5.833[/C][C]2.886[/C][C]8.78[/C][C]0[/C][/ROW]
[ROW][C]5-4[/C][C]0.748[/C][C]-0.85[/C][C]2.347[/C][C]0.867[/C][/ROW]
[ROW][C]6-4[/C][C]1.243[/C][C]-0.175[/C][C]2.661[/C][C]0.137[/C][/ROW]
[ROW][C]7-4[/C][C]1.935[/C][C]0.564[/C][C]3.306[/C][C]0.001[/C][/ROW]
[ROW][C]8-4[/C][C]2.059[/C][C]0.667[/C][C]3.451[/C][C]0[/C][/ROW]
[ROW][C]9-4[/C][C]3.111[/C][C]1.536[/C][C]4.686[/C][C]0[/C][/ROW]
[ROW][C]6-5[/C][C]0.495[/C][C]-0.949[/C][C]1.938[/C][C]0.977[/C][/ROW]
[ROW][C]7-5[/C][C]1.187[/C][C]-0.21[/C][C]2.584[/C][C]0.167[/C][/ROW]
[ROW][C]8-5[/C][C]1.311[/C][C]-0.108[/C][C]2.729[/C][C]0.095[/C][/ROW]
[ROW][C]9-5[/C][C]2.363[/C][C]0.765[/C][C]3.961[/C][C]0[/C][/ROW]
[ROW][C]7-6[/C][C]0.692[/C][C]-0.495[/C][C]1.878[/C][C]0.661[/C][/ROW]
[ROW][C]8-6[/C][C]0.816[/C][C]-0.396[/C][C]2.027[/C][C]0.466[/C][/ROW]
[ROW][C]9-6[/C][C]1.868[/C][C]0.45[/C][C]3.286[/C][C]0.002[/C][/ROW]
[ROW][C]8-7[/C][C]0.124[/C][C]-1.032[/C][C]1.28[/C][C]1[/C][/ROW]
[ROW][C]9-7[/C][C]1.176[/C][C]-0.194[/C][C]2.547[/C][C]0.157[/C][/ROW]
[ROW][C]9-8[/C][C]1.052[/C][C]-0.34[/C][C]2.444[/C][C]0.305[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10-4.822-6.814-2.8310
3-10-5.947-8.883-3.0120
4-10-3.225-4.779-1.6710
5-10-2.477-4.054-0.8990
6-10-1.982-3.377-0.5870
7-10-1.29-2.6370.0560.072
8-10-1.166-2.5350.2030.164
9-10-0.114-1.6681.441
3-2-1.125-4.3242.0740.973
4-21.597-0.4113.6050.24
5-22.3460.324.3720.011
6-22.8410.9534.7280
7-23.5321.685.3840
8-23.6561.7885.5240
9-24.7082.76.7160
4-32.722-0.2255.6690.095
5-33.4710.5116.430.009
6-33.9661.16.8310.001
7-34.6571.8147.50
8-34.7811.9287.6350
9-35.8332.8868.780
5-40.748-0.852.3470.867
6-41.243-0.1752.6610.137
7-41.9350.5643.3060.001
8-42.0590.6673.4510
9-43.1111.5364.6860
6-50.495-0.9491.9380.977
7-51.187-0.212.5840.167
8-51.311-0.1082.7290.095
9-52.3630.7653.9610
7-60.692-0.4951.8780.661
8-60.816-0.3962.0270.466
9-61.8680.453.2860.002
8-70.124-1.0321.281
9-71.176-0.1942.5470.157
9-81.052-0.342.4440.305






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group82.1270.036
170 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 2.127 & 0.036 \tabularnewline
  & 170 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]8[/C][C]2.127[/C][C]0.036[/C][/ROW]
[ROW][C] [/C][C]170[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group82.1270.036
170


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1grey111111greypearsonpearsonDefaultDefaultDefaultDefaultDefaultgrey11 ; par2 = 2no22222no11111no22 ; par3 = 0.96Pearson Chi-SquaredPearson Chi-SquaredExact Pearson Chi-Squared by SimulationTRUE300000FALSETRUE ; par4 = two.sidedFALSETRUE00000 ; par5 = unpaired1212121212 ; par6 = 0White NoiseWhite NoiseWhite NoiseWhite NoiseWhite Noise ; par7 = 0.950.95 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
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,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
'Tukey Plot'
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-leveneTest(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')