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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 computationThu, 24 Nov 2011 07:26:48 -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/2011/Nov/24/t1322137806kbuoqj0lbuo9ija.htm/, Retrieved Fri, 05 Dec 2025 05:09:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146658, Retrieved Fri, 05 Dec 2025 05:09:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact641

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]
- R  D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Moms age & 30 Months] [2011-11-24 12:23:07] [09253b89c68efd7a460a267273a9d6e3]
-   P               [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mom ages and 7 years] [2011-11-24 12:26:48] [8e78b9caec05a843a8511780bd4770d3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	6	88
3	8	94
3	8	90
3	7	73
1	5	68
2	7	80
3	8	86
3	9	86
2	9	91
1	3	79
1	9	96
3	7	92
3	9	72
3	8	96
1	6	70
3	7	86
3	8	87
3	9	88
2	7	79
2	6	90
1	8	95
1	7	85
3	8	90
1	9	115
1	9	84
3	7	79
1	4	94
2	7	97
3	7	86
2	9	111
2	7	87
3	9	98
1	10	87
3	5	68
3	6	88
1	9	82
2	9	111
1	8	75
1	6	94
2	6	95
1	5	80
1	8	95
3	8	68
2	5	94
2	6	88
1	9	84
1	8	
1	4	101
1	8	98
2	9	78
3	7	109
3	7	102
3	6	81
3	9	97
2	9	75
2	8	97
3	6	101
3	10	101
2	8	95
2	7	95
3	8	95
2	3	90
3	8	107
3	10	92
2	7	86
2	5	70
3	10	95
3	5	96
2	8	91
1	9	87
2	6	92
2	9	97
2	8	102
2	5	91
3	8	68
2	3	88
3	7	97
1	8	90
3	10	101
3	9	94
1	10	101
1	9	109
2	8	100
1	8	103
3	8	94
1	9	97
3	4	85
2	6	75
3	7	77
1	4	87
1	9	78
2	7	108
3	8	97
3	8	106
1	7	107
2	7	95
2	9	107
3	8	115
3	8	101
1	9	85
3	9	90
3	10	115
3	7	95
2	8	97
3	5	112
3	9	97
3	8	77
3	7	90
1	8	94
3	8	103
1	7	77
3	6	98
3	7	90
3	7	111
2	6	77
3	6	88
2	7	75
3	9	92
2	6	78
2	10	106
2	4	80
3	8	87
3	7	92
3	5	86
3	9	85
2	8	90
1	9	101
3	8	94
3	8	86
3	9	86
2	8	90
1	9	75
3	7	86
3	6	91
3	8	97
2	6	91
3	5	70
2	3	98
3	6	96
3	8	95
2	7	100
3	8	95
3	6	97
3	9	97
3	9	92
1	10	115
3	7	88
2	5	87
3	8	100
3	9	98
1	8	102
3	4	96

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146658&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146658&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146658&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
WISCRY7V ~ MOMAGE
means81.778-79.40311.222-8.635-80.178-79.063-79.028-79.409-79.544-79.492

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MOMAGE \tabularnewline
means & 81.778 & -79.403 & 11.222 & -8.635 & -80.178 & -79.063 & -79.028 & -79.409 & -79.544 & -79.492 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146658&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MOMAGE[/C][/ROW]
[ROW][C]means[/C][C]81.778[/C][C]-79.403[/C][C]11.222[/C][C]-8.635[/C][C]-80.178[/C][C]-79.063[/C][C]-79.028[/C][C]-79.409[/C][C]-79.544[/C][C]-79.492[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146658&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146658&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
WISCRY7V ~ MOMAGE
means81.778-79.40311.222-8.635-80.178-79.063-79.028-79.409-79.544-79.492






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MOMAGE9208476.20123164.022114.3920
Residuals14228754.51202.497 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MOMAGE & 9 & 208476.201 & 23164.022 & 114.392 & 0 \tabularnewline
Residuals & 142 & 28754.51 & 202.497 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146658&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]MOMAGE[/C][C]9[/C][C]208476.201[/C][C]23164.022[/C][C]114.392[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]142[/C][C]28754.51[/C][C]202.497[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146658&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146658&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)
MOMAGE9208476.20123164.022114.3920
Residuals14228754.51202.497






Tukey Honest Significant Difference Comparisons
difflwruprp adj
10-1-79.403-98.841-59.9650
2-111.222-6.28528.7290.558
3-1-8.635-23.3296.0590.676
4-1-80.178-103.303-57.0530
5-1-79.063-99.44-58.6870
6-1-79.028-96.076-61.980
7-1-79.409-94.456-64.3630
8-1-79.544-93.183-65.9060
9-1-79.492-94.186-64.7980
2-1090.62569.369111.8810
3-1070.76851.76289.7740
4-10-0.775-26.85425.3041
5-100.339-23.33624.0151
6-100.375-20.50521.2551
7-10-0.007-19.28619.2731
8-10-0.142-18.34418.0611
9-10-0.089-19.09518.9171
3-2-19.857-36.883-2.8310.009
4-2-91.4-116.073-66.7270
5-2-90.286-112.403-68.1680
6-2-90.25-109.345-71.1550
7-2-90.632-107.963-73.30
8-2-90.767-106.891-74.6420
9-2-90.714-107.74-73.6880
4-3-71.543-94.306-48.780
5-3-70.429-90.393-50.4640
6-3-70.393-86.947-53.8390
7-3-70.774-85.258-56.290
8-3-70.91-83.925-57.8940
9-3-70.857-84.974-56.740
5-41.114-25.67127.91
6-41.15-23.225.51
7-40.768-22.22423.7611
8-40.633-21.46422.731
9-40.686-22.07823.4491
6-50.036-21.7221.7921
7-5-0.346-20.57219.881
8-5-0.481-19.68218.7211
9-5-0.429-20.39319.5361
7-6-0.382-17.24916.4861
8-6-0.517-16.14215.1081
9-6-0.464-17.01816.091
8-7-0.135-13.54713.2771
9-7-0.083-14.56714.4011
9-80.052-12.96313.0681

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
10-1 & -79.403 & -98.841 & -59.965 & 0 \tabularnewline
2-1 & 11.222 & -6.285 & 28.729 & 0.558 \tabularnewline
3-1 & -8.635 & -23.329 & 6.059 & 0.676 \tabularnewline
4-1 & -80.178 & -103.303 & -57.053 & 0 \tabularnewline
5-1 & -79.063 & -99.44 & -58.687 & 0 \tabularnewline
6-1 & -79.028 & -96.076 & -61.98 & 0 \tabularnewline
7-1 & -79.409 & -94.456 & -64.363 & 0 \tabularnewline
8-1 & -79.544 & -93.183 & -65.906 & 0 \tabularnewline
9-1 & -79.492 & -94.186 & -64.798 & 0 \tabularnewline
2-10 & 90.625 & 69.369 & 111.881 & 0 \tabularnewline
3-10 & 70.768 & 51.762 & 89.774 & 0 \tabularnewline
4-10 & -0.775 & -26.854 & 25.304 & 1 \tabularnewline
5-10 & 0.339 & -23.336 & 24.015 & 1 \tabularnewline
6-10 & 0.375 & -20.505 & 21.255 & 1 \tabularnewline
7-10 & -0.007 & -19.286 & 19.273 & 1 \tabularnewline
8-10 & -0.142 & -18.344 & 18.061 & 1 \tabularnewline
9-10 & -0.089 & -19.095 & 18.917 & 1 \tabularnewline
3-2 & -19.857 & -36.883 & -2.831 & 0.009 \tabularnewline
4-2 & -91.4 & -116.073 & -66.727 & 0 \tabularnewline
5-2 & -90.286 & -112.403 & -68.168 & 0 \tabularnewline
6-2 & -90.25 & -109.345 & -71.155 & 0 \tabularnewline
7-2 & -90.632 & -107.963 & -73.3 & 0 \tabularnewline
8-2 & -90.767 & -106.891 & -74.642 & 0 \tabularnewline
9-2 & -90.714 & -107.74 & -73.688 & 0 \tabularnewline
4-3 & -71.543 & -94.306 & -48.78 & 0 \tabularnewline
5-3 & -70.429 & -90.393 & -50.464 & 0 \tabularnewline
6-3 & -70.393 & -86.947 & -53.839 & 0 \tabularnewline
7-3 & -70.774 & -85.258 & -56.29 & 0 \tabularnewline
8-3 & -70.91 & -83.925 & -57.894 & 0 \tabularnewline
9-3 & -70.857 & -84.974 & -56.74 & 0 \tabularnewline
5-4 & 1.114 & -25.671 & 27.9 & 1 \tabularnewline
6-4 & 1.15 & -23.2 & 25.5 & 1 \tabularnewline
7-4 & 0.768 & -22.224 & 23.761 & 1 \tabularnewline
8-4 & 0.633 & -21.464 & 22.73 & 1 \tabularnewline
9-4 & 0.686 & -22.078 & 23.449 & 1 \tabularnewline
6-5 & 0.036 & -21.72 & 21.792 & 1 \tabularnewline
7-5 & -0.346 & -20.572 & 19.88 & 1 \tabularnewline
8-5 & -0.481 & -19.682 & 18.721 & 1 \tabularnewline
9-5 & -0.429 & -20.393 & 19.536 & 1 \tabularnewline
7-6 & -0.382 & -17.249 & 16.486 & 1 \tabularnewline
8-6 & -0.517 & -16.142 & 15.108 & 1 \tabularnewline
9-6 & -0.464 & -17.018 & 16.09 & 1 \tabularnewline
8-7 & -0.135 & -13.547 & 13.277 & 1 \tabularnewline
9-7 & -0.083 & -14.567 & 14.401 & 1 \tabularnewline
9-8 & 0.052 & -12.963 & 13.068 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146658&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]10-1[/C][C]-79.403[/C][C]-98.841[/C][C]-59.965[/C][C]0[/C][/ROW]
[ROW][C]2-1[/C][C]11.222[/C][C]-6.285[/C][C]28.729[/C][C]0.558[/C][/ROW]
[ROW][C]3-1[/C][C]-8.635[/C][C]-23.329[/C][C]6.059[/C][C]0.676[/C][/ROW]
[ROW][C]4-1[/C][C]-80.178[/C][C]-103.303[/C][C]-57.053[/C][C]0[/C][/ROW]
[ROW][C]5-1[/C][C]-79.063[/C][C]-99.44[/C][C]-58.687[/C][C]0[/C][/ROW]
[ROW][C]6-1[/C][C]-79.028[/C][C]-96.076[/C][C]-61.98[/C][C]0[/C][/ROW]
[ROW][C]7-1[/C][C]-79.409[/C][C]-94.456[/C][C]-64.363[/C][C]0[/C][/ROW]
[ROW][C]8-1[/C][C]-79.544[/C][C]-93.183[/C][C]-65.906[/C][C]0[/C][/ROW]
[ROW][C]9-1[/C][C]-79.492[/C][C]-94.186[/C][C]-64.798[/C][C]0[/C][/ROW]
[ROW][C]2-10[/C][C]90.625[/C][C]69.369[/C][C]111.881[/C][C]0[/C][/ROW]
[ROW][C]3-10[/C][C]70.768[/C][C]51.762[/C][C]89.774[/C][C]0[/C][/ROW]
[ROW][C]4-10[/C][C]-0.775[/C][C]-26.854[/C][C]25.304[/C][C]1[/C][/ROW]
[ROW][C]5-10[/C][C]0.339[/C][C]-23.336[/C][C]24.015[/C][C]1[/C][/ROW]
[ROW][C]6-10[/C][C]0.375[/C][C]-20.505[/C][C]21.255[/C][C]1[/C][/ROW]
[ROW][C]7-10[/C][C]-0.007[/C][C]-19.286[/C][C]19.273[/C][C]1[/C][/ROW]
[ROW][C]8-10[/C][C]-0.142[/C][C]-18.344[/C][C]18.061[/C][C]1[/C][/ROW]
[ROW][C]9-10[/C][C]-0.089[/C][C]-19.095[/C][C]18.917[/C][C]1[/C][/ROW]
[ROW][C]3-2[/C][C]-19.857[/C][C]-36.883[/C][C]-2.831[/C][C]0.009[/C][/ROW]
[ROW][C]4-2[/C][C]-91.4[/C][C]-116.073[/C][C]-66.727[/C][C]0[/C][/ROW]
[ROW][C]5-2[/C][C]-90.286[/C][C]-112.403[/C][C]-68.168[/C][C]0[/C][/ROW]
[ROW][C]6-2[/C][C]-90.25[/C][C]-109.345[/C][C]-71.155[/C][C]0[/C][/ROW]
[ROW][C]7-2[/C][C]-90.632[/C][C]-107.963[/C][C]-73.3[/C][C]0[/C][/ROW]
[ROW][C]8-2[/C][C]-90.767[/C][C]-106.891[/C][C]-74.642[/C][C]0[/C][/ROW]
[ROW][C]9-2[/C][C]-90.714[/C][C]-107.74[/C][C]-73.688[/C][C]0[/C][/ROW]
[ROW][C]4-3[/C][C]-71.543[/C][C]-94.306[/C][C]-48.78[/C][C]0[/C][/ROW]
[ROW][C]5-3[/C][C]-70.429[/C][C]-90.393[/C][C]-50.464[/C][C]0[/C][/ROW]
[ROW][C]6-3[/C][C]-70.393[/C][C]-86.947[/C][C]-53.839[/C][C]0[/C][/ROW]
[ROW][C]7-3[/C][C]-70.774[/C][C]-85.258[/C][C]-56.29[/C][C]0[/C][/ROW]
[ROW][C]8-3[/C][C]-70.91[/C][C]-83.925[/C][C]-57.894[/C][C]0[/C][/ROW]
[ROW][C]9-3[/C][C]-70.857[/C][C]-84.974[/C][C]-56.74[/C][C]0[/C][/ROW]
[ROW][C]5-4[/C][C]1.114[/C][C]-25.671[/C][C]27.9[/C][C]1[/C][/ROW]
[ROW][C]6-4[/C][C]1.15[/C][C]-23.2[/C][C]25.5[/C][C]1[/C][/ROW]
[ROW][C]7-4[/C][C]0.768[/C][C]-22.224[/C][C]23.761[/C][C]1[/C][/ROW]
[ROW][C]8-4[/C][C]0.633[/C][C]-21.464[/C][C]22.73[/C][C]1[/C][/ROW]
[ROW][C]9-4[/C][C]0.686[/C][C]-22.078[/C][C]23.449[/C][C]1[/C][/ROW]
[ROW][C]6-5[/C][C]0.036[/C][C]-21.72[/C][C]21.792[/C][C]1[/C][/ROW]
[ROW][C]7-5[/C][C]-0.346[/C][C]-20.572[/C][C]19.88[/C][C]1[/C][/ROW]
[ROW][C]8-5[/C][C]-0.481[/C][C]-19.682[/C][C]18.721[/C][C]1[/C][/ROW]
[ROW][C]9-5[/C][C]-0.429[/C][C]-20.393[/C][C]19.536[/C][C]1[/C][/ROW]
[ROW][C]7-6[/C][C]-0.382[/C][C]-17.249[/C][C]16.486[/C][C]1[/C][/ROW]
[ROW][C]8-6[/C][C]-0.517[/C][C]-16.142[/C][C]15.108[/C][C]1[/C][/ROW]
[ROW][C]9-6[/C][C]-0.464[/C][C]-17.018[/C][C]16.09[/C][C]1[/C][/ROW]
[ROW][C]8-7[/C][C]-0.135[/C][C]-13.547[/C][C]13.277[/C][C]1[/C][/ROW]
[ROW][C]9-7[/C][C]-0.083[/C][C]-14.567[/C][C]14.401[/C][C]1[/C][/ROW]
[ROW][C]9-8[/C][C]0.052[/C][C]-12.963[/C][C]13.068[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146658&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146658&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
10-1-79.403-98.841-59.9650
2-111.222-6.28528.7290.558
3-1-8.635-23.3296.0590.676
4-1-80.178-103.303-57.0530
5-1-79.063-99.44-58.6870
6-1-79.028-96.076-61.980
7-1-79.409-94.456-64.3630
8-1-79.544-93.183-65.9060
9-1-79.492-94.186-64.7980
2-1090.62569.369111.8810
3-1070.76851.76289.7740
4-10-0.775-26.85425.3041
5-100.339-23.33624.0151
6-100.375-20.50521.2551
7-10-0.007-19.28619.2731
8-10-0.142-18.34418.0611
9-10-0.089-19.09518.9171
3-2-19.857-36.883-2.8310.009
4-2-91.4-116.073-66.7270
5-2-90.286-112.403-68.1680
6-2-90.25-109.345-71.1550
7-2-90.632-107.963-73.30
8-2-90.767-106.891-74.6420
9-2-90.714-107.74-73.6880
4-3-71.543-94.306-48.780
5-3-70.429-90.393-50.4640
6-3-70.393-86.947-53.8390
7-3-70.774-85.258-56.290
8-3-70.91-83.925-57.8940
9-3-70.857-84.974-56.740
5-41.114-25.67127.91
6-41.15-23.225.51
7-40.768-22.22423.7611
8-40.633-21.46422.731
9-40.686-22.07823.4491
6-50.036-21.7221.7921
7-5-0.346-20.57219.881
8-5-0.481-19.68218.7211
9-5-0.429-20.39319.5361
7-6-0.382-17.24916.4861
8-6-0.517-16.14215.1081
9-6-0.464-17.01816.091
8-7-0.135-13.54713.2771
9-7-0.083-14.56714.4011
9-80.052-12.96313.0681






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group94.4850
142 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 9 & 4.485 & 0 \tabularnewline
  & 142 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146658&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]9[/C][C]4.485[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]142[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146658&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146658&T=4

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group94.4850
142


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 3 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 3 ; par2 = 1 ; 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')