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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 computationTue, 18 Nov 2014 14:54:43 +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/Nov/18/t1416322506x7uyi5haieud4li.htm/, Retrieved Sun, 19 May 2024 14:47:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=256135, Retrieved Sun, 19 May 2024 14:47:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57

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]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RM D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [a] [2014-11-18 14:54:43] [fdcadbf862c9fdf43b103afd9f27ab75] [Current]
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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	6
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	100
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' @ 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=256135&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=256135&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256135&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' @ jenkins.wessa.net






ANOVA Model
MC30VRB ~ MWARM30
means54-13-12.2-6-10.364-8.3-6.903-5-3.697

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MWARM30 \tabularnewline
means & 54 & -13 & -12.2 & -6 & -10.364 & -8.3 & -6.903 & -5 & -3.697 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256135&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]54[/C][C]-13[/C][C]-12.2[/C][C]-6[/C][C]-10.364[/C][C]-8.3[/C][C]-6.903[/C][C]-5[/C][C]-3.697[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256135&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256135&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
means54-13-12.2-6-10.364-8.3-6.903-5-3.697






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM3081156.75144.5942.1280.036
Residuals15110261.22567.955 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 8 & 1156.75 & 144.594 & 2.128 & 0.036 \tabularnewline
Residuals & 151 & 10261.225 & 67.955 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256135&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]1156.75[/C][C]144.594[/C][C]2.128[/C][C]0.036[/C][/ROW]
[ROW][C]Residuals[/C][C]151[/C][C]10261.225[/C][C]67.955[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256135&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256135&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)
MWARM3081156.75144.5942.1280.036
Residuals15110261.22567.955






Tukey Honest Significant Difference Comparisons
difflwruprp adj
100-10-13-40.21114.2110.852
3-10-12.2-26.4112.0110.156
4-10-6-18.7866.7860.865
5-10-10.364-21.70.9730.103
6-10-8.3-18.3481.7480.196
7-10-6.903-16.3392.5320.347
8-10-5-14.1294.1290.731
9-10-3.697-13.0625.6680.946
3-1000.8-27.62129.2211
4-1007-20.73634.7360.997
5-1002.636-24.46229.7351
6-1004.7-21.88631.2861
7-1006.097-20.26332.4570.998
8-1008-18.25234.2520.989
9-1009.303-17.03235.6380.972
4-36.2-8.99221.3920.934
5-31.836-12.15715.831
6-33.9-9.07216.8720.99
7-35.297-7.20717.80.92
8-37.2-5.07419.4740.651
9-38.503-3.94820.9540.444
5-4-4.364-16.9088.1810.974
6-4-2.3-13.6949.0940.999
7-4-0.903-11.769.9541
8-41-9.59211.5921
9-42.303-8.49313.0990.999
6-52.064-7.67611.8030.999
7-53.46-5.64512.5660.956
8-55.364-3.42414.1510.6
9-56.667-2.36615.70.335
7-61.397-6.0448.8381
8-63.3-3.74910.3490.866
9-64.603-2.74911.9550.566
8-71.903-4.248.0470.988
9-73.206-3.2839.6960.827
9-81.303-4.7327.3380.999

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
100-10 & -13 & -40.211 & 14.211 & 0.852 \tabularnewline
3-10 & -12.2 & -26.411 & 2.011 & 0.156 \tabularnewline
4-10 & -6 & -18.786 & 6.786 & 0.865 \tabularnewline
5-10 & -10.364 & -21.7 & 0.973 & 0.103 \tabularnewline
6-10 & -8.3 & -18.348 & 1.748 & 0.196 \tabularnewline
7-10 & -6.903 & -16.339 & 2.532 & 0.347 \tabularnewline
8-10 & -5 & -14.129 & 4.129 & 0.731 \tabularnewline
9-10 & -3.697 & -13.062 & 5.668 & 0.946 \tabularnewline
3-100 & 0.8 & -27.621 & 29.221 & 1 \tabularnewline
4-100 & 7 & -20.736 & 34.736 & 0.997 \tabularnewline
5-100 & 2.636 & -24.462 & 29.735 & 1 \tabularnewline
6-100 & 4.7 & -21.886 & 31.286 & 1 \tabularnewline
7-100 & 6.097 & -20.263 & 32.457 & 0.998 \tabularnewline
8-100 & 8 & -18.252 & 34.252 & 0.989 \tabularnewline
9-100 & 9.303 & -17.032 & 35.638 & 0.972 \tabularnewline
4-3 & 6.2 & -8.992 & 21.392 & 0.934 \tabularnewline
5-3 & 1.836 & -12.157 & 15.83 & 1 \tabularnewline
6-3 & 3.9 & -9.072 & 16.872 & 0.99 \tabularnewline
7-3 & 5.297 & -7.207 & 17.8 & 0.92 \tabularnewline
8-3 & 7.2 & -5.074 & 19.474 & 0.651 \tabularnewline
9-3 & 8.503 & -3.948 & 20.954 & 0.444 \tabularnewline
5-4 & -4.364 & -16.908 & 8.181 & 0.974 \tabularnewline
6-4 & -2.3 & -13.694 & 9.094 & 0.999 \tabularnewline
7-4 & -0.903 & -11.76 & 9.954 & 1 \tabularnewline
8-4 & 1 & -9.592 & 11.592 & 1 \tabularnewline
9-4 & 2.303 & -8.493 & 13.099 & 0.999 \tabularnewline
6-5 & 2.064 & -7.676 & 11.803 & 0.999 \tabularnewline
7-5 & 3.46 & -5.645 & 12.566 & 0.956 \tabularnewline
8-5 & 5.364 & -3.424 & 14.151 & 0.6 \tabularnewline
9-5 & 6.667 & -2.366 & 15.7 & 0.335 \tabularnewline
7-6 & 1.397 & -6.044 & 8.838 & 1 \tabularnewline
8-6 & 3.3 & -3.749 & 10.349 & 0.866 \tabularnewline
9-6 & 4.603 & -2.749 & 11.955 & 0.566 \tabularnewline
8-7 & 1.903 & -4.24 & 8.047 & 0.988 \tabularnewline
9-7 & 3.206 & -3.283 & 9.696 & 0.827 \tabularnewline
9-8 & 1.303 & -4.732 & 7.338 & 0.999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256135&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]100-10[/C][C]-13[/C][C]-40.211[/C][C]14.211[/C][C]0.852[/C][/ROW]
[ROW][C]3-10[/C][C]-12.2[/C][C]-26.411[/C][C]2.011[/C][C]0.156[/C][/ROW]
[ROW][C]4-10[/C][C]-6[/C][C]-18.786[/C][C]6.786[/C][C]0.865[/C][/ROW]
[ROW][C]5-10[/C][C]-10.364[/C][C]-21.7[/C][C]0.973[/C][C]0.103[/C][/ROW]
[ROW][C]6-10[/C][C]-8.3[/C][C]-18.348[/C][C]1.748[/C][C]0.196[/C][/ROW]
[ROW][C]7-10[/C][C]-6.903[/C][C]-16.339[/C][C]2.532[/C][C]0.347[/C][/ROW]
[ROW][C]8-10[/C][C]-5[/C][C]-14.129[/C][C]4.129[/C][C]0.731[/C][/ROW]
[ROW][C]9-10[/C][C]-3.697[/C][C]-13.062[/C][C]5.668[/C][C]0.946[/C][/ROW]
[ROW][C]3-100[/C][C]0.8[/C][C]-27.621[/C][C]29.221[/C][C]1[/C][/ROW]
[ROW][C]4-100[/C][C]7[/C][C]-20.736[/C][C]34.736[/C][C]0.997[/C][/ROW]
[ROW][C]5-100[/C][C]2.636[/C][C]-24.462[/C][C]29.735[/C][C]1[/C][/ROW]
[ROW][C]6-100[/C][C]4.7[/C][C]-21.886[/C][C]31.286[/C][C]1[/C][/ROW]
[ROW][C]7-100[/C][C]6.097[/C][C]-20.263[/C][C]32.457[/C][C]0.998[/C][/ROW]
[ROW][C]8-100[/C][C]8[/C][C]-18.252[/C][C]34.252[/C][C]0.989[/C][/ROW]
[ROW][C]9-100[/C][C]9.303[/C][C]-17.032[/C][C]35.638[/C][C]0.972[/C][/ROW]
[ROW][C]4-3[/C][C]6.2[/C][C]-8.992[/C][C]21.392[/C][C]0.934[/C][/ROW]
[ROW][C]5-3[/C][C]1.836[/C][C]-12.157[/C][C]15.83[/C][C]1[/C][/ROW]
[ROW][C]6-3[/C][C]3.9[/C][C]-9.072[/C][C]16.872[/C][C]0.99[/C][/ROW]
[ROW][C]7-3[/C][C]5.297[/C][C]-7.207[/C][C]17.8[/C][C]0.92[/C][/ROW]
[ROW][C]8-3[/C][C]7.2[/C][C]-5.074[/C][C]19.474[/C][C]0.651[/C][/ROW]
[ROW][C]9-3[/C][C]8.503[/C][C]-3.948[/C][C]20.954[/C][C]0.444[/C][/ROW]
[ROW][C]5-4[/C][C]-4.364[/C][C]-16.908[/C][C]8.181[/C][C]0.974[/C][/ROW]
[ROW][C]6-4[/C][C]-2.3[/C][C]-13.694[/C][C]9.094[/C][C]0.999[/C][/ROW]
[ROW][C]7-4[/C][C]-0.903[/C][C]-11.76[/C][C]9.954[/C][C]1[/C][/ROW]
[ROW][C]8-4[/C][C]1[/C][C]-9.592[/C][C]11.592[/C][C]1[/C][/ROW]
[ROW][C]9-4[/C][C]2.303[/C][C]-8.493[/C][C]13.099[/C][C]0.999[/C][/ROW]
[ROW][C]6-5[/C][C]2.064[/C][C]-7.676[/C][C]11.803[/C][C]0.999[/C][/ROW]
[ROW][C]7-5[/C][C]3.46[/C][C]-5.645[/C][C]12.566[/C][C]0.956[/C][/ROW]
[ROW][C]8-5[/C][C]5.364[/C][C]-3.424[/C][C]14.151[/C][C]0.6[/C][/ROW]
[ROW][C]9-5[/C][C]6.667[/C][C]-2.366[/C][C]15.7[/C][C]0.335[/C][/ROW]
[ROW][C]7-6[/C][C]1.397[/C][C]-6.044[/C][C]8.838[/C][C]1[/C][/ROW]
[ROW][C]8-6[/C][C]3.3[/C][C]-3.749[/C][C]10.349[/C][C]0.866[/C][/ROW]
[ROW][C]9-6[/C][C]4.603[/C][C]-2.749[/C][C]11.955[/C][C]0.566[/C][/ROW]
[ROW][C]8-7[/C][C]1.903[/C][C]-4.24[/C][C]8.047[/C][C]0.988[/C][/ROW]
[ROW][C]9-7[/C][C]3.206[/C][C]-3.283[/C][C]9.696[/C][C]0.827[/C][/ROW]
[ROW][C]9-8[/C][C]1.303[/C][C]-4.732[/C][C]7.338[/C][C]0.999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256135&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256135&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
100-10-13-40.21114.2110.852
3-10-12.2-26.4112.0110.156
4-10-6-18.7866.7860.865
5-10-10.364-21.70.9730.103
6-10-8.3-18.3481.7480.196
7-10-6.903-16.3392.5320.347
8-10-5-14.1294.1290.731
9-10-3.697-13.0625.6680.946
3-1000.8-27.62129.2211
4-1007-20.73634.7360.997
5-1002.636-24.46229.7351
6-1004.7-21.88631.2861
7-1006.097-20.26332.4570.998
8-1008-18.25234.2520.989
9-1009.303-17.03235.6380.972
4-36.2-8.99221.3920.934
5-31.836-12.15715.831
6-33.9-9.07216.8720.99
7-35.297-7.20717.80.92
8-37.2-5.07419.4740.651
9-38.503-3.94820.9540.444
5-4-4.364-16.9088.1810.974
6-4-2.3-13.6949.0940.999
7-4-0.903-11.769.9541
8-41-9.59211.5921
9-42.303-8.49313.0990.999
6-52.064-7.67611.8030.999
7-53.46-5.64512.5660.956
8-55.364-3.42414.1510.6
9-56.667-2.36615.70.335
7-61.397-6.0448.8381
8-63.3-3.74910.3490.866
9-64.603-2.74911.9550.566
8-71.903-4.248.0470.988
9-73.206-3.2839.6960.827
9-81.303-4.7327.3380.999






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group80.7890.613
151 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 0.789 & 0.613 \tabularnewline
  & 151 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256135&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]0.789[/C][C]0.613[/C][/ROW]
[ROW][C] [/C][C]151[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256135&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256135&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)
Group80.7890.613
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()
}
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<-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')