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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software ModuleIan.Hollidayrwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationMon, 29 Nov 2010 23:38:11 +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/2010/Nov/30/t1291073880p69eiyohf8iuvoz.htm/, Retrieved Mon, 29 Apr 2024 16:33:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103189, Retrieved Mon, 29 Apr 2024 16:33:14 +0000
QR Codes:

Original text written by user:MC30VRB MWARM30
IsPrivate?No (this computation is public)
User-defined keywordsAVONVA TEST
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
-             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8] [2010-11-29 22:37:06] [b57c483c9c7aeaac92ee0309919c11c0]
-    D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8] [2010-11-29 22:49:28] [b57c483c9c7aeaac92ee0309919c11c0]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8] [2010-11-29 23:03:13] [b57c483c9c7aeaac92ee0309919c11c0]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8] [2010-11-29 23:21:18] [b57c483c9c7aeaac92ee0309919c11c0]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8] [2010-11-29 23:38:11] [4ce57d25edbdd6fa8e41e5f59df13410] [Current]
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8] [2010-11-29 23:49:22] [b57c483c9c7aeaac92ee0309919c11c0]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	3
36	6
56	8
48	8
32	7
44	5
39	7
34	8
41	9
50	9
39	3
62	9
52	7
37	9
50	8
41	6
55	7
41	8
56	9
39	7
52	6
46	8
44	7
48	7
41	8
50	9
50	9
44	7
52	4
54	7
44	7
52	9
37	7
52	9
50	10
36	5
50	6
52	9
55	9
31	8
36	6
49	6
42	5
37	8
41	8
30	5
52	6
30	9
41	8
44	4
66	8
48	9
43	7
57	7
46	6
54	9
48	9
48	8
52	4
62	6
58	10
58	8
62	7
48	7
46	8
34	3
66	8
52	10
55	7
55	5
57	10
56	5
55	8
56	9
54	6
55	9
46	8
52	5
32	8
44	3
46	7
59	8
46	10
46	9
54	10
66	9
56	8
59	8
57	8
52	9
48	4
44	6
41	7
50	4
48	9
48	7
59	8
34	0
46	8
54	7
55	7
54	9
59	8
44	8
54	9
52	9
66	10
44	7
57	8
39	5
60	9
45	8
41	7
50	8
39	8
43	7
48	6
37	7
58	7
46	6
43	6
44	7
34	9
30	6
50	10
39	4
37	8
55	7
48	10
41	0
39	5
36	9
43	8
50	9
55	8
43	8
60	9
48	8
30	9
43	7
39	6
52	8
39	6
39	5
56	3
59	6
46	8
57	7
50	8
54	6
50	9
60	9
59	10
41	7
48	5
59	8
60	9
56	8
56	8
51	4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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' @ 72.249.127.135 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103189&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' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103189&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103189&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






ANOVA Model
MC30VRB ~ MWARM30
means37.516.54.310.56.1368.8169.59711.512.803

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MWARM30 \tabularnewline
means & 37.5 & 16.5 & 4.3 & 10.5 & 6.136 & 8.816 & 9.597 & 11.5 & 12.803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103189&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]37.5[/C][C]16.5[/C][C]4.3[/C][C]10.5[/C][C]6.136[/C][C]8.816[/C][C]9.597[/C][C]11.5[/C][C]12.803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103189&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103189&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
MC30VRB ~ MWARM30
means37.516.54.310.56.1368.8169.59711.512.803






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM3081276.345159.5432.3750.019
Residuals15110141.6367.163 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 8 & 1276.345 & 159.543 & 2.375 & 0.019 \tabularnewline
Residuals & 151 & 10141.63 & 67.163 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103189&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]MWARM30[/C][C]8[/C][C]1276.345[/C][C]159.543[/C][C]2.375[/C][C]0.019[/C][/ROW]
[ROW][C]Residuals[/C][C]151[/C][C]10141.63[/C][C]67.163[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103189&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103189&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)
MWARM3081276.345159.5432.3750.019
Residuals15110141.6367.163






Tukey Honest Significant Difference Comparisons
difflwruprp adj
10-016.5-3.47936.4790.196
3-04.3-17.2825.880.999
4-010.5-10.18131.1810.805
5-06.136-13.69125.9640.988
6-08.816-10.35927.990.877
7-09.597-9.22128.4150.801
8-011.5-7.16830.1680.588
9-012.803-5.9831.5860.447
3-10-12.2-26.3281.9280.15
4-10-6-18.7116.7110.861
5-10-10.364-21.6340.9060.098
6-10-7.684-17.7612.3930.292
7-10-6.903-16.2842.4770.339
8-10-5-14.0764.0760.725
9-10-3.697-13.0085.6140.944
4-36.2-8.90321.3030.932
5-31.836-12.07515.7481
6-34.516-8.44917.480.974
7-35.297-7.13417.7270.917
8-37.2-5.00219.4020.644
9-38.503-3.87520.8810.436
5-4-4.364-16.8358.1070.973
6-4-1.684-13.0889.721
7-4-0.903-11.6979.891
8-41-9.5311.531
9-42.303-8.4313.0360.999
6-52.679-7.09312.4520.994
7-53.46-5.59212.5130.955
8-55.364-3.37314.10.593
9-56.667-2.31315.6470.327
7-60.781-6.7348.2961
8-62.684-4.4479.8160.959
9-63.987-3.44111.4150.752
8-71.903-4.2048.0110.987
9-73.206-3.2459.6580.822
9-81.303-4.6977.3030.999

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
10-0 & 16.5 & -3.479 & 36.479 & 0.196 \tabularnewline
3-0 & 4.3 & -17.28 & 25.88 & 0.999 \tabularnewline
4-0 & 10.5 & -10.181 & 31.181 & 0.805 \tabularnewline
5-0 & 6.136 & -13.691 & 25.964 & 0.988 \tabularnewline
6-0 & 8.816 & -10.359 & 27.99 & 0.877 \tabularnewline
7-0 & 9.597 & -9.221 & 28.415 & 0.801 \tabularnewline
8-0 & 11.5 & -7.168 & 30.168 & 0.588 \tabularnewline
9-0 & 12.803 & -5.98 & 31.586 & 0.447 \tabularnewline
3-10 & -12.2 & -26.328 & 1.928 & 0.15 \tabularnewline
4-10 & -6 & -18.711 & 6.711 & 0.861 \tabularnewline
5-10 & -10.364 & -21.634 & 0.906 & 0.098 \tabularnewline
6-10 & -7.684 & -17.761 & 2.393 & 0.292 \tabularnewline
7-10 & -6.903 & -16.284 & 2.477 & 0.339 \tabularnewline
8-10 & -5 & -14.076 & 4.076 & 0.725 \tabularnewline
9-10 & -3.697 & -13.008 & 5.614 & 0.944 \tabularnewline
4-3 & 6.2 & -8.903 & 21.303 & 0.932 \tabularnewline
5-3 & 1.836 & -12.075 & 15.748 & 1 \tabularnewline
6-3 & 4.516 & -8.449 & 17.48 & 0.974 \tabularnewline
7-3 & 5.297 & -7.134 & 17.727 & 0.917 \tabularnewline
8-3 & 7.2 & -5.002 & 19.402 & 0.644 \tabularnewline
9-3 & 8.503 & -3.875 & 20.881 & 0.436 \tabularnewline
5-4 & -4.364 & -16.835 & 8.107 & 0.973 \tabularnewline
6-4 & -1.684 & -13.088 & 9.72 & 1 \tabularnewline
7-4 & -0.903 & -11.697 & 9.89 & 1 \tabularnewline
8-4 & 1 & -9.53 & 11.53 & 1 \tabularnewline
9-4 & 2.303 & -8.43 & 13.036 & 0.999 \tabularnewline
6-5 & 2.679 & -7.093 & 12.452 & 0.994 \tabularnewline
7-5 & 3.46 & -5.592 & 12.513 & 0.955 \tabularnewline
8-5 & 5.364 & -3.373 & 14.1 & 0.593 \tabularnewline
9-5 & 6.667 & -2.313 & 15.647 & 0.327 \tabularnewline
7-6 & 0.781 & -6.734 & 8.296 & 1 \tabularnewline
8-6 & 2.684 & -4.447 & 9.816 & 0.959 \tabularnewline
9-6 & 3.987 & -3.441 & 11.415 & 0.752 \tabularnewline
8-7 & 1.903 & -4.204 & 8.011 & 0.987 \tabularnewline
9-7 & 3.206 & -3.245 & 9.658 & 0.822 \tabularnewline
9-8 & 1.303 & -4.697 & 7.303 & 0.999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103189&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]10-0[/C][C]16.5[/C][C]-3.479[/C][C]36.479[/C][C]0.196[/C][/ROW]
[ROW][C]3-0[/C][C]4.3[/C][C]-17.28[/C][C]25.88[/C][C]0.999[/C][/ROW]
[ROW][C]4-0[/C][C]10.5[/C][C]-10.181[/C][C]31.181[/C][C]0.805[/C][/ROW]
[ROW][C]5-0[/C][C]6.136[/C][C]-13.691[/C][C]25.964[/C][C]0.988[/C][/ROW]
[ROW][C]6-0[/C][C]8.816[/C][C]-10.359[/C][C]27.99[/C][C]0.877[/C][/ROW]
[ROW][C]7-0[/C][C]9.597[/C][C]-9.221[/C][C]28.415[/C][C]0.801[/C][/ROW]
[ROW][C]8-0[/C][C]11.5[/C][C]-7.168[/C][C]30.168[/C][C]0.588[/C][/ROW]
[ROW][C]9-0[/C][C]12.803[/C][C]-5.98[/C][C]31.586[/C][C]0.447[/C][/ROW]
[ROW][C]3-10[/C][C]-12.2[/C][C]-26.328[/C][C]1.928[/C][C]0.15[/C][/ROW]
[ROW][C]4-10[/C][C]-6[/C][C]-18.711[/C][C]6.711[/C][C]0.861[/C][/ROW]
[ROW][C]5-10[/C][C]-10.364[/C][C]-21.634[/C][C]0.906[/C][C]0.098[/C][/ROW]
[ROW][C]6-10[/C][C]-7.684[/C][C]-17.761[/C][C]2.393[/C][C]0.292[/C][/ROW]
[ROW][C]7-10[/C][C]-6.903[/C][C]-16.284[/C][C]2.477[/C][C]0.339[/C][/ROW]
[ROW][C]8-10[/C][C]-5[/C][C]-14.076[/C][C]4.076[/C][C]0.725[/C][/ROW]
[ROW][C]9-10[/C][C]-3.697[/C][C]-13.008[/C][C]5.614[/C][C]0.944[/C][/ROW]
[ROW][C]4-3[/C][C]6.2[/C][C]-8.903[/C][C]21.303[/C][C]0.932[/C][/ROW]
[ROW][C]5-3[/C][C]1.836[/C][C]-12.075[/C][C]15.748[/C][C]1[/C][/ROW]
[ROW][C]6-3[/C][C]4.516[/C][C]-8.449[/C][C]17.48[/C][C]0.974[/C][/ROW]
[ROW][C]7-3[/C][C]5.297[/C][C]-7.134[/C][C]17.727[/C][C]0.917[/C][/ROW]
[ROW][C]8-3[/C][C]7.2[/C][C]-5.002[/C][C]19.402[/C][C]0.644[/C][/ROW]
[ROW][C]9-3[/C][C]8.503[/C][C]-3.875[/C][C]20.881[/C][C]0.436[/C][/ROW]
[ROW][C]5-4[/C][C]-4.364[/C][C]-16.835[/C][C]8.107[/C][C]0.973[/C][/ROW]
[ROW][C]6-4[/C][C]-1.684[/C][C]-13.088[/C][C]9.72[/C][C]1[/C][/ROW]
[ROW][C]7-4[/C][C]-0.903[/C][C]-11.697[/C][C]9.89[/C][C]1[/C][/ROW]
[ROW][C]8-4[/C][C]1[/C][C]-9.53[/C][C]11.53[/C][C]1[/C][/ROW]
[ROW][C]9-4[/C][C]2.303[/C][C]-8.43[/C][C]13.036[/C][C]0.999[/C][/ROW]
[ROW][C]6-5[/C][C]2.679[/C][C]-7.093[/C][C]12.452[/C][C]0.994[/C][/ROW]
[ROW][C]7-5[/C][C]3.46[/C][C]-5.592[/C][C]12.513[/C][C]0.955[/C][/ROW]
[ROW][C]8-5[/C][C]5.364[/C][C]-3.373[/C][C]14.1[/C][C]0.593[/C][/ROW]
[ROW][C]9-5[/C][C]6.667[/C][C]-2.313[/C][C]15.647[/C][C]0.327[/C][/ROW]
[ROW][C]7-6[/C][C]0.781[/C][C]-6.734[/C][C]8.296[/C][C]1[/C][/ROW]
[ROW][C]8-6[/C][C]2.684[/C][C]-4.447[/C][C]9.816[/C][C]0.959[/C][/ROW]
[ROW][C]9-6[/C][C]3.987[/C][C]-3.441[/C][C]11.415[/C][C]0.752[/C][/ROW]
[ROW][C]8-7[/C][C]1.903[/C][C]-4.204[/C][C]8.011[/C][C]0.987[/C][/ROW]
[ROW][C]9-7[/C][C]3.206[/C][C]-3.245[/C][C]9.658[/C][C]0.822[/C][/ROW]
[ROW][C]9-8[/C][C]1.303[/C][C]-4.697[/C][C]7.303[/C][C]0.999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103189&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103189&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
10-016.5-3.47936.4790.196
3-04.3-17.2825.880.999
4-010.5-10.18131.1810.805
5-06.136-13.69125.9640.988
6-08.816-10.35927.990.877
7-09.597-9.22128.4150.801
8-011.5-7.16830.1680.588
9-012.803-5.9831.5860.447
3-10-12.2-26.3281.9280.15
4-10-6-18.7116.7110.861
5-10-10.364-21.6340.9060.098
6-10-7.684-17.7612.3930.292
7-10-6.903-16.2842.4770.339
8-10-5-14.0764.0760.725
9-10-3.697-13.0085.6140.944
4-36.2-8.90321.3030.932
5-31.836-12.07515.7481
6-34.516-8.44917.480.974
7-35.297-7.13417.7270.917
8-37.2-5.00219.4020.644
9-38.503-3.87520.8810.436
5-4-4.364-16.8358.1070.973
6-4-1.684-13.0889.721
7-4-0.903-11.6979.891
8-41-9.5311.531
9-42.303-8.4313.0360.999
6-52.679-7.09312.4520.994
7-53.46-5.59212.5130.955
8-55.364-3.37314.10.593
9-56.667-2.31315.6470.327
7-60.781-6.7348.2961
8-62.684-4.4479.8160.959
9-63.987-3.44111.4150.752
8-71.903-4.2048.0110.987
9-73.206-3.2459.6580.822
9-81.303-4.6977.3030.999






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group80.6630.724
151 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 0.663 & 0.724 \tabularnewline
  & 151 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103189&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]0.663[/C][C]0.724[/C][/ROW]
[ROW][C] [/C][C]151[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103189&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103189&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)
Group80.6630.724
151


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
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){
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
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<-levene.test(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')