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R Software Module

rwasp_Two Factor ANOVA.wasp

Title produced by software

Two-Way ANOVA

Date of computation

Sun, 27 Nov 2016 15:48:07 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Nov/27/t1480258184zedwpqjmde3bty6.htm/, Retrieved Mon, 29 Apr 2024 20:46:33 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297192, Retrieved Mon, 29 Apr 2024 20:46:33 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Two-Way ANOVA] [Klantentevredenhe...] [2016-11-27 14:48:07] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	Big 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 time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297192&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]

4 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=297192&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297192&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	Big Analytics Cloud Computing Center

ANOVA Model
Response ~ Treatment_A * Treatment_B
means	4.667	-0.417	-0.517	-0.667	-0.667	-0.167	0.142	0.16	0.167	0.167

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 4.667 & -0.417 & -0.517 & -0.667 & -0.667 & -0.167 & 0.142 & 0.16 & 0.167 & 0.167 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297192&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]4.667[/C][C]-0.417[/C][C]-0.517[/C][C]-0.667[/C][C]-0.667[/C][C]-0.167[/C][C]0.142[/C][C]0.16[/C][C]0.167[/C][C]0.167[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297192&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297192&T=1

As an alternative you can also use a QR Code:

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

ANOVA Model
Response ~ Treatment_A * Treatment_B
means	4.667	-0.417	-0.517	-0.667	-0.667	-0.167	0.142	0.16	0.167	0.167

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	4
Treatment_A	4	4.164	1.041	2.613	0.037
Treatment_B	4	0.035	0.035	0.087	0.768
Treatment_A:Treatment_B	4	0.093	0.023	0.059	0.994
Residuals	156	62.148	0.398

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 4 &  &  &  &  \tabularnewline
Treatment_A & 4 & 4.164 & 1.041 & 2.613 & 0.037 \tabularnewline
Treatment_B & 4 & 0.035 & 0.035 & 0.087 & 0.768 \tabularnewline
Treatment_A:Treatment_B & 4 & 0.093 & 0.023 & 0.059 & 0.994 \tabularnewline
Residuals & 156 & 62.148 & 0.398 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297192&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][/C][C]4[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]4[/C][C]4.164[/C][C]1.041[/C][C]2.613[/C][C]0.037[/C][/ROW]
[ROW][C]Treatment_B[/C][C]4[/C][C]0.035[/C][C]0.035[/C][C]0.087[/C][C]0.768[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]4[/C][C]0.093[/C][C]0.023[/C][C]0.059[/C][C]0.994[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]62.148[/C][C]0.398[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297192&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297192&T=2

As an alternative you can also use a QR Code:

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

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	4
Treatment_A	4	4.164	1.041	2.613	0.037
Treatment_B	4	0.035	0.035	0.087	0.768
Treatment_A:Treatment_B	4	0.093	0.023	0.059	0.994
Residuals	156	62.148	0.398

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
2-1	-0.349	-0.823	0.124	0.253
3-1	-0.442	-0.934	0.049	0.1
4-1	-0.588	-1.12	-0.056	0.022
5-1	-0.588	-1.474	0.298	0.359
3-2	-0.093	-0.422	0.236	0.936
4-2	-0.239	-0.626	0.148	0.436
5-2	-0.239	-1.046	0.569	0.925
4-3	-0.146	-0.556	0.264	0.863
5-3	-0.146	-0.964	0.673	0.988
5-4	0	-0.844	0.844	1
2-1	-0.029	-0.222	0.165	0.77
2:1-1:1	-0.417	-1.172	0.338	0.752
3:1-1:1	-0.517	-1.33	0.297	0.573
4:1-1:1	-0.667	-1.545	0.212	0.312
5:1-1:1	-0.667	-2.017	0.684	0.854
1:2-1:1	-0.167	-1.151	0.818	1
2:2-1:1	-0.441	-1.208	0.326	0.706
3:2-1:1	-0.524	-1.3	0.253	0.485
4:2-1:1	-0.667	-1.511	0.178	0.258
5:2-1:1	-0.667	-2.251	0.917	0.94
3:1-2:1	-0.1	-0.665	0.465	1
4:1-2:1	-0.25	-0.906	0.406	0.967
5:1-2:1	-0.25	-1.468	0.968	1
1:2-2:1	0.25	-0.542	1.042	0.991
2:2-2:1	-0.024	-0.521	0.472	1
3:2-2:1	-0.107	-0.618	0.403	1
4:2-2:1	-0.25	-0.859	0.359	0.948
5:2-2:1	-0.25	-1.722	1.222	1
4:1-3:1	-0.15	-0.872	0.572	1
5:1-3:1	-0.15	-1.404	1.104	1
1:2-3:1	0.35	-0.498	1.198	0.946
2:2-3:1	0.076	-0.505	0.657	1
3:2-3:1	-0.007	-0.6	0.586	1
4:2-3:1	-0.15	-0.83	0.53	0.999
5:2-3:1	-0.15	-1.653	1.353	1
5:1-4:1	0	-1.298	1.298	1
1:2-4:1	0.5	-0.41	1.41	0.757
2:2-4:1	0.226	-0.444	0.895	0.986
3:2-4:1	0.143	-0.537	0.823	1
4:2-4:1	0	-0.757	0.757	1
5:2-4:1	0	-1.539	1.539	1
1:2-5:1	0.5	-0.872	1.872	0.976
2:2-5:1	0.226	-0.999	1.451	1
3:2-5:1	0.143	-1.088	1.374	1
4:2-5:1	0	-1.275	1.275	1
5:2-5:1	0	-1.85	1.85	1
2:2-1:2	-0.274	-1.078	0.529	0.985
3:2-1:2	-0.357	-1.169	0.455	0.922
4:2-1:2	-0.5	-1.377	0.377	0.716
5:2-1:2	-0.5	-2.102	1.102	0.992
3:2-2:2	-0.083	-0.611	0.445	1
4:2-2:2	-0.226	-0.85	0.398	0.977
5:2-2:2	-0.226	-1.704	1.252	1
4:2-3:2	-0.143	-0.778	0.492	0.999
5:2-3:2	-0.143	-1.626	1.34	1
5:2-4:2	0	-1.52	1.52	1

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & -0.349 & -0.823 & 0.124 & 0.253 \tabularnewline
3-1 & -0.442 & -0.934 & 0.049 & 0.1 \tabularnewline
4-1 & -0.588 & -1.12 & -0.056 & 0.022 \tabularnewline
5-1 & -0.588 & -1.474 & 0.298 & 0.359 \tabularnewline
3-2 & -0.093 & -0.422 & 0.236 & 0.936 \tabularnewline
4-2 & -0.239 & -0.626 & 0.148 & 0.436 \tabularnewline
5-2 & -0.239 & -1.046 & 0.569 & 0.925 \tabularnewline
4-3 & -0.146 & -0.556 & 0.264 & 0.863 \tabularnewline
5-3 & -0.146 & -0.964 & 0.673 & 0.988 \tabularnewline
5-4 & 0 & -0.844 & 0.844 & 1 \tabularnewline
2-1 & -0.029 & -0.222 & 0.165 & 0.77 \tabularnewline
2:1-1:1 & -0.417 & -1.172 & 0.338 & 0.752 \tabularnewline
3:1-1:1 & -0.517 & -1.33 & 0.297 & 0.573 \tabularnewline
4:1-1:1 & -0.667 & -1.545 & 0.212 & 0.312 \tabularnewline
5:1-1:1 & -0.667 & -2.017 & 0.684 & 0.854 \tabularnewline
1:2-1:1 & -0.167 & -1.151 & 0.818 & 1 \tabularnewline
2:2-1:1 & -0.441 & -1.208 & 0.326 & 0.706 \tabularnewline
3:2-1:1 & -0.524 & -1.3 & 0.253 & 0.485 \tabularnewline
4:2-1:1 & -0.667 & -1.511 & 0.178 & 0.258 \tabularnewline
5:2-1:1 & -0.667 & -2.251 & 0.917 & 0.94 \tabularnewline
3:1-2:1 & -0.1 & -0.665 & 0.465 & 1 \tabularnewline
4:1-2:1 & -0.25 & -0.906 & 0.406 & 0.967 \tabularnewline
5:1-2:1 & -0.25 & -1.468 & 0.968 & 1 \tabularnewline
1:2-2:1 & 0.25 & -0.542 & 1.042 & 0.991 \tabularnewline
2:2-2:1 & -0.024 & -0.521 & 0.472 & 1 \tabularnewline
3:2-2:1 & -0.107 & -0.618 & 0.403 & 1 \tabularnewline
4:2-2:1 & -0.25 & -0.859 & 0.359 & 0.948 \tabularnewline
5:2-2:1 & -0.25 & -1.722 & 1.222 & 1 \tabularnewline
4:1-3:1 & -0.15 & -0.872 & 0.572 & 1 \tabularnewline
5:1-3:1 & -0.15 & -1.404 & 1.104 & 1 \tabularnewline
1:2-3:1 & 0.35 & -0.498 & 1.198 & 0.946 \tabularnewline
2:2-3:1 & 0.076 & -0.505 & 0.657 & 1 \tabularnewline
3:2-3:1 & -0.007 & -0.6 & 0.586 & 1 \tabularnewline
4:2-3:1 & -0.15 & -0.83 & 0.53 & 0.999 \tabularnewline
5:2-3:1 & -0.15 & -1.653 & 1.353 & 1 \tabularnewline
5:1-4:1 & 0 & -1.298 & 1.298 & 1 \tabularnewline
1:2-4:1 & 0.5 & -0.41 & 1.41 & 0.757 \tabularnewline
2:2-4:1 & 0.226 & -0.444 & 0.895 & 0.986 \tabularnewline
3:2-4:1 & 0.143 & -0.537 & 0.823 & 1 \tabularnewline
4:2-4:1 & 0 & -0.757 & 0.757 & 1 \tabularnewline
5:2-4:1 & 0 & -1.539 & 1.539 & 1 \tabularnewline
1:2-5:1 & 0.5 & -0.872 & 1.872 & 0.976 \tabularnewline
2:2-5:1 & 0.226 & -0.999 & 1.451 & 1 \tabularnewline
3:2-5:1 & 0.143 & -1.088 & 1.374 & 1 \tabularnewline
4:2-5:1 & 0 & -1.275 & 1.275 & 1 \tabularnewline
5:2-5:1 & 0 & -1.85 & 1.85 & 1 \tabularnewline
2:2-1:2 & -0.274 & -1.078 & 0.529 & 0.985 \tabularnewline
3:2-1:2 & -0.357 & -1.169 & 0.455 & 0.922 \tabularnewline
4:2-1:2 & -0.5 & -1.377 & 0.377 & 0.716 \tabularnewline
5:2-1:2 & -0.5 & -2.102 & 1.102 & 0.992 \tabularnewline
3:2-2:2 & -0.083 & -0.611 & 0.445 & 1 \tabularnewline
4:2-2:2 & -0.226 & -0.85 & 0.398 & 0.977 \tabularnewline
5:2-2:2 & -0.226 & -1.704 & 1.252 & 1 \tabularnewline
4:2-3:2 & -0.143 & -0.778 & 0.492 & 0.999 \tabularnewline
5:2-3:2 & -0.143 & -1.626 & 1.34 & 1 \tabularnewline
5:2-4:2 & 0 & -1.52 & 1.52 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297192&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]2-1[/C][C]-0.349[/C][C]-0.823[/C][C]0.124[/C][C]0.253[/C][/ROW]
[ROW][C]3-1[/C][C]-0.442[/C][C]-0.934[/C][C]0.049[/C][C]0.1[/C][/ROW]
[ROW][C]4-1[/C][C]-0.588[/C][C]-1.12[/C][C]-0.056[/C][C]0.022[/C][/ROW]
[ROW][C]5-1[/C][C]-0.588[/C][C]-1.474[/C][C]0.298[/C][C]0.359[/C][/ROW]
[ROW][C]3-2[/C][C]-0.093[/C][C]-0.422[/C][C]0.236[/C][C]0.936[/C][/ROW]
[ROW][C]4-2[/C][C]-0.239[/C][C]-0.626[/C][C]0.148[/C][C]0.436[/C][/ROW]
[ROW][C]5-2[/C][C]-0.239[/C][C]-1.046[/C][C]0.569[/C][C]0.925[/C][/ROW]
[ROW][C]4-3[/C][C]-0.146[/C][C]-0.556[/C][C]0.264[/C][C]0.863[/C][/ROW]
[ROW][C]5-3[/C][C]-0.146[/C][C]-0.964[/C][C]0.673[/C][C]0.988[/C][/ROW]
[ROW][C]5-4[/C][C]0[/C][C]-0.844[/C][C]0.844[/C][C]1[/C][/ROW]
[ROW][C]2-1[/C][C]-0.029[/C][C]-0.222[/C][C]0.165[/C][C]0.77[/C][/ROW]
[ROW][C]2:1-1:1[/C][C]-0.417[/C][C]-1.172[/C][C]0.338[/C][C]0.752[/C][/ROW]
[ROW][C]3:1-1:1[/C][C]-0.517[/C][C]-1.33[/C][C]0.297[/C][C]0.573[/C][/ROW]
[ROW][C]4:1-1:1[/C][C]-0.667[/C][C]-1.545[/C][C]0.212[/C][C]0.312[/C][/ROW]
[ROW][C]5:1-1:1[/C][C]-0.667[/C][C]-2.017[/C][C]0.684[/C][C]0.854[/C][/ROW]
[ROW][C]1:2-1:1[/C][C]-0.167[/C][C]-1.151[/C][C]0.818[/C][C]1[/C][/ROW]
[ROW][C]2:2-1:1[/C][C]-0.441[/C][C]-1.208[/C][C]0.326[/C][C]0.706[/C][/ROW]
[ROW][C]3:2-1:1[/C][C]-0.524[/C][C]-1.3[/C][C]0.253[/C][C]0.485[/C][/ROW]
[ROW][C]4:2-1:1[/C][C]-0.667[/C][C]-1.511[/C][C]0.178[/C][C]0.258[/C][/ROW]
[ROW][C]5:2-1:1[/C][C]-0.667[/C][C]-2.251[/C][C]0.917[/C][C]0.94[/C][/ROW]
[ROW][C]3:1-2:1[/C][C]-0.1[/C][C]-0.665[/C][C]0.465[/C][C]1[/C][/ROW]
[ROW][C]4:1-2:1[/C][C]-0.25[/C][C]-0.906[/C][C]0.406[/C][C]0.967[/C][/ROW]
[ROW][C]5:1-2:1[/C][C]-0.25[/C][C]-1.468[/C][C]0.968[/C][C]1[/C][/ROW]
[ROW][C]1:2-2:1[/C][C]0.25[/C][C]-0.542[/C][C]1.042[/C][C]0.991[/C][/ROW]
[ROW][C]2:2-2:1[/C][C]-0.024[/C][C]-0.521[/C][C]0.472[/C][C]1[/C][/ROW]
[ROW][C]3:2-2:1[/C][C]-0.107[/C][C]-0.618[/C][C]0.403[/C][C]1[/C][/ROW]
[ROW][C]4:2-2:1[/C][C]-0.25[/C][C]-0.859[/C][C]0.359[/C][C]0.948[/C][/ROW]
[ROW][C]5:2-2:1[/C][C]-0.25[/C][C]-1.722[/C][C]1.222[/C][C]1[/C][/ROW]
[ROW][C]4:1-3:1[/C][C]-0.15[/C][C]-0.872[/C][C]0.572[/C][C]1[/C][/ROW]
[ROW][C]5:1-3:1[/C][C]-0.15[/C][C]-1.404[/C][C]1.104[/C][C]1[/C][/ROW]
[ROW][C]1:2-3:1[/C][C]0.35[/C][C]-0.498[/C][C]1.198[/C][C]0.946[/C][/ROW]
[ROW][C]2:2-3:1[/C][C]0.076[/C][C]-0.505[/C][C]0.657[/C][C]1[/C][/ROW]
[ROW][C]3:2-3:1[/C][C]-0.007[/C][C]-0.6[/C][C]0.586[/C][C]1[/C][/ROW]
[ROW][C]4:2-3:1[/C][C]-0.15[/C][C]-0.83[/C][C]0.53[/C][C]0.999[/C][/ROW]
[ROW][C]5:2-3:1[/C][C]-0.15[/C][C]-1.653[/C][C]1.353[/C][C]1[/C][/ROW]
[ROW][C]5:1-4:1[/C][C]0[/C][C]-1.298[/C][C]1.298[/C][C]1[/C][/ROW]
[ROW][C]1:2-4:1[/C][C]0.5[/C][C]-0.41[/C][C]1.41[/C][C]0.757[/C][/ROW]
[ROW][C]2:2-4:1[/C][C]0.226[/C][C]-0.444[/C][C]0.895[/C][C]0.986[/C][/ROW]
[ROW][C]3:2-4:1[/C][C]0.143[/C][C]-0.537[/C][C]0.823[/C][C]1[/C][/ROW]
[ROW][C]4:2-4:1[/C][C]0[/C][C]-0.757[/C][C]0.757[/C][C]1[/C][/ROW]
[ROW][C]5:2-4:1[/C][C]0[/C][C]-1.539[/C][C]1.539[/C][C]1[/C][/ROW]
[ROW][C]1:2-5:1[/C][C]0.5[/C][C]-0.872[/C][C]1.872[/C][C]0.976[/C][/ROW]
[ROW][C]2:2-5:1[/C][C]0.226[/C][C]-0.999[/C][C]1.451[/C][C]1[/C][/ROW]
[ROW][C]3:2-5:1[/C][C]0.143[/C][C]-1.088[/C][C]1.374[/C][C]1[/C][/ROW]
[ROW][C]4:2-5:1[/C][C]0[/C][C]-1.275[/C][C]1.275[/C][C]1[/C][/ROW]
[ROW][C]5:2-5:1[/C][C]0[/C][C]-1.85[/C][C]1.85[/C][C]1[/C][/ROW]
[ROW][C]2:2-1:2[/C][C]-0.274[/C][C]-1.078[/C][C]0.529[/C][C]0.985[/C][/ROW]
[ROW][C]3:2-1:2[/C][C]-0.357[/C][C]-1.169[/C][C]0.455[/C][C]0.922[/C][/ROW]
[ROW][C]4:2-1:2[/C][C]-0.5[/C][C]-1.377[/C][C]0.377[/C][C]0.716[/C][/ROW]
[ROW][C]5:2-1:2[/C][C]-0.5[/C][C]-2.102[/C][C]1.102[/C][C]0.992[/C][/ROW]
[ROW][C]3:2-2:2[/C][C]-0.083[/C][C]-0.611[/C][C]0.445[/C][C]1[/C][/ROW]
[ROW][C]4:2-2:2[/C][C]-0.226[/C][C]-0.85[/C][C]0.398[/C][C]0.977[/C][/ROW]
[ROW][C]5:2-2:2[/C][C]-0.226[/C][C]-1.704[/C][C]1.252[/C][C]1[/C][/ROW]
[ROW][C]4:2-3:2[/C][C]-0.143[/C][C]-0.778[/C][C]0.492[/C][C]0.999[/C][/ROW]
[ROW][C]5:2-3:2[/C][C]-0.143[/C][C]-1.626[/C][C]1.34[/C][C]1[/C][/ROW]
[ROW][C]5:2-4:2[/C][C]0[/C][C]-1.52[/C][C]1.52[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297192&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297192&T=3

As an alternative you can also use a QR Code:

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

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
2-1	-0.349	-0.823	0.124	0.253
3-1	-0.442	-0.934	0.049	0.1
4-1	-0.588	-1.12	-0.056	0.022
5-1	-0.588	-1.474	0.298	0.359
3-2	-0.093	-0.422	0.236	0.936
4-2	-0.239	-0.626	0.148	0.436
5-2	-0.239	-1.046	0.569	0.925
4-3	-0.146	-0.556	0.264	0.863
5-3	-0.146	-0.964	0.673	0.988
5-4	0	-0.844	0.844	1
2-1	-0.029	-0.222	0.165	0.77
2:1-1:1	-0.417	-1.172	0.338	0.752
3:1-1:1	-0.517	-1.33	0.297	0.573
4:1-1:1	-0.667	-1.545	0.212	0.312
5:1-1:1	-0.667	-2.017	0.684	0.854
1:2-1:1	-0.167	-1.151	0.818	1
2:2-1:1	-0.441	-1.208	0.326	0.706
3:2-1:1	-0.524	-1.3	0.253	0.485
4:2-1:1	-0.667	-1.511	0.178	0.258
5:2-1:1	-0.667	-2.251	0.917	0.94
3:1-2:1	-0.1	-0.665	0.465	1
4:1-2:1	-0.25	-0.906	0.406	0.967
5:1-2:1	-0.25	-1.468	0.968	1
1:2-2:1	0.25	-0.542	1.042	0.991
2:2-2:1	-0.024	-0.521	0.472	1
3:2-2:1	-0.107	-0.618	0.403	1
4:2-2:1	-0.25	-0.859	0.359	0.948
5:2-2:1	-0.25	-1.722	1.222	1
4:1-3:1	-0.15	-0.872	0.572	1
5:1-3:1	-0.15	-1.404	1.104	1
1:2-3:1	0.35	-0.498	1.198	0.946
2:2-3:1	0.076	-0.505	0.657	1
3:2-3:1	-0.007	-0.6	0.586	1
4:2-3:1	-0.15	-0.83	0.53	0.999
5:2-3:1	-0.15	-1.653	1.353	1
5:1-4:1	0	-1.298	1.298	1
1:2-4:1	0.5	-0.41	1.41	0.757
2:2-4:1	0.226	-0.444	0.895	0.986
3:2-4:1	0.143	-0.537	0.823	1
4:2-4:1	0	-0.757	0.757	1
5:2-4:1	0	-1.539	1.539	1
1:2-5:1	0.5	-0.872	1.872	0.976
2:2-5:1	0.226	-0.999	1.451	1
3:2-5:1	0.143	-1.088	1.374	1
4:2-5:1	0	-1.275	1.275	1
5:2-5:1	0	-1.85	1.85	1
2:2-1:2	-0.274	-1.078	0.529	0.985
3:2-1:2	-0.357	-1.169	0.455	0.922
4:2-1:2	-0.5	-1.377	0.377	0.716
5:2-1:2	-0.5	-2.102	1.102	0.992
3:2-2:2	-0.083	-0.611	0.445	1
4:2-2:2	-0.226	-0.85	0.398	0.977
5:2-2:2	-0.226	-1.704	1.252	1
4:2-3:2	-0.143	-0.778	0.492	0.999
5:2-3:2	-0.143	-1.626	1.34	1
5:2-4:2	0	-1.52	1.52	1

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	9	0.735	0.676
	156

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 9 & 0.735 & 0.676 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297192&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]0.735[/C][C]0.676[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297192&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297192&T=4

As an alternative you can also use a QR Code:

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

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	9	0.735	0.676
	156

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;

Parameters (R input):

par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;

R code (references can be found in the software module):

cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
cat3 <- as.numeric(par3)
intercept<-as.logical(par4)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
f2 <- as.character(x[,cat3])
xdf<-data.frame(x1,f1, f2)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
(V3 <-dimnames(y)[[1]][cat3])
names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, 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$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, lmxdf$call['formula'],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$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
for(i in 1 : length(rownames(anova.xdf))-1){
a<-table.row.start(a)
a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], 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$'Df'[i+1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
dev.off()
bitmap(file='designplot.png')
xdf2 <- xdf # to preserve xdf make copy for function
names(xdf2) <- c(V1, V2, V3)
plot.design(xdf2, main='Design Plot of Group Means')
dev.off()
bitmap(file='interactionplot.png')
interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups')
dev.off()
if(intercept==TRUE){
thsd<-TukeyHSD(aov.xdf)
names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep=''))
bitmap(file='TukeyHSDPlot.png')
layout(matrix(c(1,2,3,3), 2,2))
plot(thsd, las=1)
dev.off()
}
if(intercept==TRUE){
ntables<-length(names(thsd))
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(nt in 1:ntables){
for(i in 1:length(rownames(thsd[[nt]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
} # end nt
a<-table.end(a)
table.save(a,file='hsdtable.tab')
}#end if hsd tables
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code