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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationWed, 07 Dec 2016 14:07:28 +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/2016/Dec/07/t1481116140t6b9o5efmm7j535.htm/, Retrieved Fri, 01 Nov 2024 03:47:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298083, Retrieved Fri, 01 Nov 2024 03:47:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [2-way ANOVA-EP1 e...] [2016-12-07 13:07:28] [55eb8f21ed24cda91766c505eb72bb6f] [Current]
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Dataseries X:
13	5	"'m'"
16	3	"'v'"
17	5	"'v'"
NA	5	"'v'"
NA	5	"'m'"
16	5	"'v'"
NA	5	"'v'"
NA	5	"'v'"
NA	5	"'m'"
17	5	"'m'"
17	4	"'m'"
15	2	"'m'"
16	5	"'m'"
14	4	"'m'"
16	5	"'m'"
17	4	"'v'"
NA	5	"'m'"
NA	5	"'v'"
NA	5	"'v'"
NA	4	"'v'"
16	4	"'v'"
NA	3	"'m'"
16	5	"'v'"
NA	4	"'v'"
NA	5	"'m'"
NA	4	"'m'"
16	5	"'m'"
15	5	"'m'"
16	5	"'m'"
16	5	"'m'"
13	5	"'m'"
15	5	"'v'"
17	5	"'m'"
NA	5	"'m'"
13	5	"'v'"
17	4	"'m'"
NA	4	"'m'"
14	5	"'v'"
14	5	"'m'"
18	5	"'m'"
NA	5	"'v'"
17	5	"'v'"
13	5	"'v'"
16	5	"'v'"
15	5	"'v'"
15	5	"'v'"
NA	5	"'v'"
15	NA	"'v'"
13	4	"'v'"
NA	5	"'m'"
17	5	"'v'"
NA	4	"'m'"
NA	5	"'v'"
11	3	"'v'"
14	4	"'m'"
13	3	"'v'"
NA	5	"'m'"
17	5	"'m'"
16	5	"'v'"
NA	5	"'m'"
17	5	"'v'"
16	5	"'v'"
16	5	"'v'"
16	5	"'v'"
15	4	"'m'"
12	5	"'v'"
17	4	"'m'"
14	5	"'v'"
14	2	"'m'"
16	4	"'v'"
NA	5	"'v'"
NA	5	"'v'"
NA	4	"'m'"
NA	5	"'v'"
NA	2	"'m'"
15	5	"'v'"
16	3	"'m'"
14	4	"'v'"
15	4	"'m'"
17	5	"'v'"
NA	5	"'v'"
10	4	"'m'"
NA	4	"'m'"
17	5	"'m'"
NA	4	"'v'"
20	4	"'v'"
17	5	"'v'"
18	5	"'v'"
NA	5	"'v'"
17	4	"'m'"
14	4	"'v'"
NA	4	"'m'"
17	3	"'m'"
NA	4	"'m'"
17	5	"'m'"
NA	5	"'v'"
16	4	"'v'"
18	5	"'v'"
18	2	"'m'"
16	5	"'v'"
NA	5	"'v'"
NA	4	"'m'"
15	3	"'m'"
13	5	"'v'"
NA	4	"'v'"
NA	5	"'v'"
NA	5	"'v'"
NA	5	"'m'"
NA	5	"'m'"
16	5	"'m'"
NA	4	"'v'"
NA	5	"'v'"
NA	5	"'v'"
12	5	"'m'"
NA	4	"'m'"
16	5	"'v'"
16	5	"'m'"
NA	2	"'m'"
16	5	"'v'"
14	5	"'m'"
15	5	"'m'"
14	5	"'m'"
NA	5	"'v'"
15	5	"'v'"
NA	5	"'v'"
15	5	"'v'"
16	4	"'v'"
NA	3	"'m'"
NA	5	"'m'"
NA	5	"'v'"
11	5	"'v'"
NA	5	"'v'"
18	4	"'m'"
NA	4	"'v'"
11	4	"'m'"
NA	5	"'m'"
18	4	"'m'"
NA	NA	"'m'"
15	4	"'v'"
19	5	"'m'"
17	2	"'m'"
NA	5	"'m'"
14	4	"'m'"
NA	5	"'v'"
13	5	"'m'"
17	4	"'v'"
14	5	"'v'"
19	4	"'v'"
14	5	"'v'"
NA	5	"'m'"
NA	5	"'m'"
16	4	"'m'"
16	5	"'m'"
15	5	"'v'"
12	5	"'v'"
NA	5	"'v'"
17	5	"'v'"
NA	2	"'m'"
NA	5	"'v'"
18	3	"'m'"
15	5	"'v'"
18	5	"'m'"
15	5	"'m'"
NA	4	"'m'"
NA	5	"'m'"
NA	5	"'m'"
16	5	"'v'"
NA	5	"'v'"
16	5	"'m'"




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298083&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=298083&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298083&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 Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Response ~ Treatment_A * Treatment_B
means160.5-0.786-0.37-0.66-0.34-2.8271.209NANA

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 16 & 0.5 & -0.786 & -0.37 & -0.66 & -0.34 & -2.827 & 1.209 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298083&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]16[/C][C]0.5[/C][C]-0.786[/C][C]-0.37[/C][C]-0.66[/C][C]-0.34[/C][C]-2.827[/C][C]1.209[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298083&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298083&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
means160.5-0.786-0.37-0.66-0.34-2.8271.209NANA







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
4
Treatment_A42.740.6850.1970.94
Treatment_B41.1211.1210.3220.572
Treatment_A:Treatment_B422.77611.3883.2680.042
Residuals95331.0533.485

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 4 &  &  &  &  \tabularnewline
Treatment_A & 4 & 2.74 & 0.685 & 0.197 & 0.94 \tabularnewline
Treatment_B & 4 & 1.121 & 1.121 & 0.322 & 0.572 \tabularnewline
Treatment_A:Treatment_B & 4 & 22.776 & 11.388 & 3.268 & 0.042 \tabularnewline
Residuals & 95 & 331.053 & 3.485 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298083&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]2.74[/C][C]0.685[/C][C]0.197[/C][C]0.94[/C][/ROW]
[ROW][C]Treatment_B[/C][C]4[/C][C]1.121[/C][C]1.121[/C][C]0.322[/C][C]0.572[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]4[/C][C]22.776[/C][C]11.388[/C][C]3.268[/C][C]0.042[/C][/ROW]
[ROW][C]Residuals[/C][C]95[/C][C]331.053[/C][C]3.485[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298083&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298083&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
DfSum SqMean SqF valuePr(>F)
4
Treatment_A42.740.6850.1970.94
Treatment_B41.1211.1210.3220.572
Treatment_A:Treatment_B422.77611.3883.2680.042
Residuals95331.0533.485







Tukey Honest Significant Difference Comparisons
difflwruprp adj
3-2-0.857-4.1112.3970.948
4-2-0.385-3.1732.4030.995
5-2-0.569-3.2432.1050.976
NA-2-1-6.8044.8040.989
4-30.473-1.7382.6830.976
5-30.288-1.7772.3530.995
NA-3-0.143-5.6925.4071
5-4-0.185-1.3891.020.993
NA-4-0.615-5.9054.6750.998
NA-5-0.431-5.6624.80.999
'v'-'m'-0.202-0.9330.5290.585
3:'m'-2:'m'0.5-3.7774.7771
4:'m'-2:'m'-0.786-4.2152.6430.999
5:'m'-2:'m'-0.37-3.6112.871
NA:'m'-2:'m'NANANANA
2:'v'-2:'m'NANANANA
3:'v'-2:'m'-2.667-7.2861.9530.689
4:'v'-2:'m'0.083-3.4093.5751
5:'v'-2:'m'-0.711-3.892.4690.999
NA:'v'-2:'m'-1-7.7625.7621
4:'m'-3:'m'-1.286-4.7152.1430.968
5:'m'-3:'m'-0.87-4.1112.370.997
NA:'m'-3:'m'NANANANA
2:'v'-3:'m'NANANANA
3:'v'-3:'m'-3.167-7.7861.4530.45
4:'v'-3:'m'-0.417-3.9093.0751
5:'v'-3:'m'-1.211-4.391.9690.965
NA:'v'-3:'m'-1.5-8.2625.2620.999
5:'m'-4:'m'0.415-1.5772.4071
NA:'m'-4:'m'NANANANA
2:'v'-4:'m'NANANANA
3:'v'-4:'m'-1.881-5.7291.9670.853
4:'v'-4:'m'0.869-1.513.2490.973
5:'v'-4:'m'0.075-1.8161.9661
NA:'v'-4:'m'-0.214-6.4756.0471
NA:'m'-5:'m'NANANANA
2:'v'-5:'m'NANANANA
3:'v'-5:'m'-2.296-5.9771.3850.587
4:'v'-5:'m'0.454-1.6452.5520.999
5:'v'-5:'m'-0.34-1.8631.1820.999
NA:'v'-5:'m'-0.63-6.7895.531
2:'v'-NA:'m'NANANANA
3:'v'-NA:'m'NANANANA
4:'v'-NA:'m'NANANANA
5:'v'-NA:'m'NANANANA
NA:'v'-NA:'m'NANANANA
3:'v'-2:'v'NANANANA
4:'v'-2:'v'NANANANA
5:'v'-2:'v'NANANANA
NA:'v'-2:'v'NANANANA
4:'v'-3:'v'2.75-1.1546.6540.41
5:'v'-3:'v'1.956-1.6715.5830.766
NA:'v'-3:'v'1.667-5.3188.6510.999
5:'v'-4:'v'-0.794-2.7971.2090.955
NA:'v'-4:'v'-1.083-7.3795.2121
NA:'v'-5:'v'-0.289-6.4175.8381

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
3-2 & -0.857 & -4.111 & 2.397 & 0.948 \tabularnewline
4-2 & -0.385 & -3.173 & 2.403 & 0.995 \tabularnewline
5-2 & -0.569 & -3.243 & 2.105 & 0.976 \tabularnewline
NA-2 & -1 & -6.804 & 4.804 & 0.989 \tabularnewline
4-3 & 0.473 & -1.738 & 2.683 & 0.976 \tabularnewline
5-3 & 0.288 & -1.777 & 2.353 & 0.995 \tabularnewline
NA-3 & -0.143 & -5.692 & 5.407 & 1 \tabularnewline
5-4 & -0.185 & -1.389 & 1.02 & 0.993 \tabularnewline
NA-4 & -0.615 & -5.905 & 4.675 & 0.998 \tabularnewline
NA-5 & -0.431 & -5.662 & 4.8 & 0.999 \tabularnewline
'v'-'m' & -0.202 & -0.933 & 0.529 & 0.585 \tabularnewline
3:'m'-2:'m' & 0.5 & -3.777 & 4.777 & 1 \tabularnewline
4:'m'-2:'m' & -0.786 & -4.215 & 2.643 & 0.999 \tabularnewline
5:'m'-2:'m' & -0.37 & -3.611 & 2.87 & 1 \tabularnewline
NA:'m'-2:'m' & NA & NA & NA & NA \tabularnewline
2:'v'-2:'m' & NA & NA & NA & NA \tabularnewline
3:'v'-2:'m' & -2.667 & -7.286 & 1.953 & 0.689 \tabularnewline
4:'v'-2:'m' & 0.083 & -3.409 & 3.575 & 1 \tabularnewline
5:'v'-2:'m' & -0.711 & -3.89 & 2.469 & 0.999 \tabularnewline
NA:'v'-2:'m' & -1 & -7.762 & 5.762 & 1 \tabularnewline
4:'m'-3:'m' & -1.286 & -4.715 & 2.143 & 0.968 \tabularnewline
5:'m'-3:'m' & -0.87 & -4.111 & 2.37 & 0.997 \tabularnewline
NA:'m'-3:'m' & NA & NA & NA & NA \tabularnewline
2:'v'-3:'m' & NA & NA & NA & NA \tabularnewline
3:'v'-3:'m' & -3.167 & -7.786 & 1.453 & 0.45 \tabularnewline
4:'v'-3:'m' & -0.417 & -3.909 & 3.075 & 1 \tabularnewline
5:'v'-3:'m' & -1.211 & -4.39 & 1.969 & 0.965 \tabularnewline
NA:'v'-3:'m' & -1.5 & -8.262 & 5.262 & 0.999 \tabularnewline
5:'m'-4:'m' & 0.415 & -1.577 & 2.407 & 1 \tabularnewline
NA:'m'-4:'m' & NA & NA & NA & NA \tabularnewline
2:'v'-4:'m' & NA & NA & NA & NA \tabularnewline
3:'v'-4:'m' & -1.881 & -5.729 & 1.967 & 0.853 \tabularnewline
4:'v'-4:'m' & 0.869 & -1.51 & 3.249 & 0.973 \tabularnewline
5:'v'-4:'m' & 0.075 & -1.816 & 1.966 & 1 \tabularnewline
NA:'v'-4:'m' & -0.214 & -6.475 & 6.047 & 1 \tabularnewline
NA:'m'-5:'m' & NA & NA & NA & NA \tabularnewline
2:'v'-5:'m' & NA & NA & NA & NA \tabularnewline
3:'v'-5:'m' & -2.296 & -5.977 & 1.385 & 0.587 \tabularnewline
4:'v'-5:'m' & 0.454 & -1.645 & 2.552 & 0.999 \tabularnewline
5:'v'-5:'m' & -0.34 & -1.863 & 1.182 & 0.999 \tabularnewline
NA:'v'-5:'m' & -0.63 & -6.789 & 5.53 & 1 \tabularnewline
2:'v'-NA:'m' & NA & NA & NA & NA \tabularnewline
3:'v'-NA:'m' & NA & NA & NA & NA \tabularnewline
4:'v'-NA:'m' & NA & NA & NA & NA \tabularnewline
5:'v'-NA:'m' & NA & NA & NA & NA \tabularnewline
NA:'v'-NA:'m' & NA & NA & NA & NA \tabularnewline
3:'v'-2:'v' & NA & NA & NA & NA \tabularnewline
4:'v'-2:'v' & NA & NA & NA & NA \tabularnewline
5:'v'-2:'v' & NA & NA & NA & NA \tabularnewline
NA:'v'-2:'v' & NA & NA & NA & NA \tabularnewline
4:'v'-3:'v' & 2.75 & -1.154 & 6.654 & 0.41 \tabularnewline
5:'v'-3:'v' & 1.956 & -1.671 & 5.583 & 0.766 \tabularnewline
NA:'v'-3:'v' & 1.667 & -5.318 & 8.651 & 0.999 \tabularnewline
5:'v'-4:'v' & -0.794 & -2.797 & 1.209 & 0.955 \tabularnewline
NA:'v'-4:'v' & -1.083 & -7.379 & 5.212 & 1 \tabularnewline
NA:'v'-5:'v' & -0.289 & -6.417 & 5.838 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298083&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]3-2[/C][C]-0.857[/C][C]-4.111[/C][C]2.397[/C][C]0.948[/C][/ROW]
[ROW][C]4-2[/C][C]-0.385[/C][C]-3.173[/C][C]2.403[/C][C]0.995[/C][/ROW]
[ROW][C]5-2[/C][C]-0.569[/C][C]-3.243[/C][C]2.105[/C][C]0.976[/C][/ROW]
[ROW][C]NA-2[/C][C]-1[/C][C]-6.804[/C][C]4.804[/C][C]0.989[/C][/ROW]
[ROW][C]4-3[/C][C]0.473[/C][C]-1.738[/C][C]2.683[/C][C]0.976[/C][/ROW]
[ROW][C]5-3[/C][C]0.288[/C][C]-1.777[/C][C]2.353[/C][C]0.995[/C][/ROW]
[ROW][C]NA-3[/C][C]-0.143[/C][C]-5.692[/C][C]5.407[/C][C]1[/C][/ROW]
[ROW][C]5-4[/C][C]-0.185[/C][C]-1.389[/C][C]1.02[/C][C]0.993[/C][/ROW]
[ROW][C]NA-4[/C][C]-0.615[/C][C]-5.905[/C][C]4.675[/C][C]0.998[/C][/ROW]
[ROW][C]NA-5[/C][C]-0.431[/C][C]-5.662[/C][C]4.8[/C][C]0.999[/C][/ROW]
[ROW][C]'v'-'m'[/C][C]-0.202[/C][C]-0.933[/C][C]0.529[/C][C]0.585[/C][/ROW]
[ROW][C]3:'m'-2:'m'[/C][C]0.5[/C][C]-3.777[/C][C]4.777[/C][C]1[/C][/ROW]
[ROW][C]4:'m'-2:'m'[/C][C]-0.786[/C][C]-4.215[/C][C]2.643[/C][C]0.999[/C][/ROW]
[ROW][C]5:'m'-2:'m'[/C][C]-0.37[/C][C]-3.611[/C][C]2.87[/C][C]1[/C][/ROW]
[ROW][C]NA:'m'-2:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]2:'v'-2:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]3:'v'-2:'m'[/C][C]-2.667[/C][C]-7.286[/C][C]1.953[/C][C]0.689[/C][/ROW]
[ROW][C]4:'v'-2:'m'[/C][C]0.083[/C][C]-3.409[/C][C]3.575[/C][C]1[/C][/ROW]
[ROW][C]5:'v'-2:'m'[/C][C]-0.711[/C][C]-3.89[/C][C]2.469[/C][C]0.999[/C][/ROW]
[ROW][C]NA:'v'-2:'m'[/C][C]-1[/C][C]-7.762[/C][C]5.762[/C][C]1[/C][/ROW]
[ROW][C]4:'m'-3:'m'[/C][C]-1.286[/C][C]-4.715[/C][C]2.143[/C][C]0.968[/C][/ROW]
[ROW][C]5:'m'-3:'m'[/C][C]-0.87[/C][C]-4.111[/C][C]2.37[/C][C]0.997[/C][/ROW]
[ROW][C]NA:'m'-3:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]2:'v'-3:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]3:'v'-3:'m'[/C][C]-3.167[/C][C]-7.786[/C][C]1.453[/C][C]0.45[/C][/ROW]
[ROW][C]4:'v'-3:'m'[/C][C]-0.417[/C][C]-3.909[/C][C]3.075[/C][C]1[/C][/ROW]
[ROW][C]5:'v'-3:'m'[/C][C]-1.211[/C][C]-4.39[/C][C]1.969[/C][C]0.965[/C][/ROW]
[ROW][C]NA:'v'-3:'m'[/C][C]-1.5[/C][C]-8.262[/C][C]5.262[/C][C]0.999[/C][/ROW]
[ROW][C]5:'m'-4:'m'[/C][C]0.415[/C][C]-1.577[/C][C]2.407[/C][C]1[/C][/ROW]
[ROW][C]NA:'m'-4:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]2:'v'-4:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]3:'v'-4:'m'[/C][C]-1.881[/C][C]-5.729[/C][C]1.967[/C][C]0.853[/C][/ROW]
[ROW][C]4:'v'-4:'m'[/C][C]0.869[/C][C]-1.51[/C][C]3.249[/C][C]0.973[/C][/ROW]
[ROW][C]5:'v'-4:'m'[/C][C]0.075[/C][C]-1.816[/C][C]1.966[/C][C]1[/C][/ROW]
[ROW][C]NA:'v'-4:'m'[/C][C]-0.214[/C][C]-6.475[/C][C]6.047[/C][C]1[/C][/ROW]
[ROW][C]NA:'m'-5:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]2:'v'-5:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]3:'v'-5:'m'[/C][C]-2.296[/C][C]-5.977[/C][C]1.385[/C][C]0.587[/C][/ROW]
[ROW][C]4:'v'-5:'m'[/C][C]0.454[/C][C]-1.645[/C][C]2.552[/C][C]0.999[/C][/ROW]
[ROW][C]5:'v'-5:'m'[/C][C]-0.34[/C][C]-1.863[/C][C]1.182[/C][C]0.999[/C][/ROW]
[ROW][C]NA:'v'-5:'m'[/C][C]-0.63[/C][C]-6.789[/C][C]5.53[/C][C]1[/C][/ROW]
[ROW][C]2:'v'-NA:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]3:'v'-NA:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]4:'v'-NA:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]5:'v'-NA:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]NA:'v'-NA:'m'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]3:'v'-2:'v'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]4:'v'-2:'v'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]5:'v'-2:'v'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]NA:'v'-2:'v'[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]4:'v'-3:'v'[/C][C]2.75[/C][C]-1.154[/C][C]6.654[/C][C]0.41[/C][/ROW]
[ROW][C]5:'v'-3:'v'[/C][C]1.956[/C][C]-1.671[/C][C]5.583[/C][C]0.766[/C][/ROW]
[ROW][C]NA:'v'-3:'v'[/C][C]1.667[/C][C]-5.318[/C][C]8.651[/C][C]0.999[/C][/ROW]
[ROW][C]5:'v'-4:'v'[/C][C]-0.794[/C][C]-2.797[/C][C]1.209[/C][C]0.955[/C][/ROW]
[ROW][C]NA:'v'-4:'v'[/C][C]-1.083[/C][C]-7.379[/C][C]5.212[/C][C]1[/C][/ROW]
[ROW][C]NA:'v'-5:'v'[/C][C]-0.289[/C][C]-6.417[/C][C]5.838[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298083&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298083&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
difflwruprp adj
3-2-0.857-4.1112.3970.948
4-2-0.385-3.1732.4030.995
5-2-0.569-3.2432.1050.976
NA-2-1-6.8044.8040.989
4-30.473-1.7382.6830.976
5-30.288-1.7772.3530.995
NA-3-0.143-5.6925.4071
5-4-0.185-1.3891.020.993
NA-4-0.615-5.9054.6750.998
NA-5-0.431-5.6624.80.999
'v'-'m'-0.202-0.9330.5290.585
3:'m'-2:'m'0.5-3.7774.7771
4:'m'-2:'m'-0.786-4.2152.6430.999
5:'m'-2:'m'-0.37-3.6112.871
NA:'m'-2:'m'NANANANA
2:'v'-2:'m'NANANANA
3:'v'-2:'m'-2.667-7.2861.9530.689
4:'v'-2:'m'0.083-3.4093.5751
5:'v'-2:'m'-0.711-3.892.4690.999
NA:'v'-2:'m'-1-7.7625.7621
4:'m'-3:'m'-1.286-4.7152.1430.968
5:'m'-3:'m'-0.87-4.1112.370.997
NA:'m'-3:'m'NANANANA
2:'v'-3:'m'NANANANA
3:'v'-3:'m'-3.167-7.7861.4530.45
4:'v'-3:'m'-0.417-3.9093.0751
5:'v'-3:'m'-1.211-4.391.9690.965
NA:'v'-3:'m'-1.5-8.2625.2620.999
5:'m'-4:'m'0.415-1.5772.4071
NA:'m'-4:'m'NANANANA
2:'v'-4:'m'NANANANA
3:'v'-4:'m'-1.881-5.7291.9670.853
4:'v'-4:'m'0.869-1.513.2490.973
5:'v'-4:'m'0.075-1.8161.9661
NA:'v'-4:'m'-0.214-6.4756.0471
NA:'m'-5:'m'NANANANA
2:'v'-5:'m'NANANANA
3:'v'-5:'m'-2.296-5.9771.3850.587
4:'v'-5:'m'0.454-1.6452.5520.999
5:'v'-5:'m'-0.34-1.8631.1820.999
NA:'v'-5:'m'-0.63-6.7895.531
2:'v'-NA:'m'NANANANA
3:'v'-NA:'m'NANANANA
4:'v'-NA:'m'NANANANA
5:'v'-NA:'m'NANANANA
NA:'v'-NA:'m'NANANANA
3:'v'-2:'v'NANANANA
4:'v'-2:'v'NANANANA
5:'v'-2:'v'NANANANA
NA:'v'-2:'v'NANANANA
4:'v'-3:'v'2.75-1.1546.6540.41
5:'v'-3:'v'1.956-1.6715.5830.766
NA:'v'-3:'v'1.667-5.3188.6510.999
5:'v'-4:'v'-0.794-2.7971.2090.955
NA:'v'-4:'v'-1.083-7.3795.2121
NA:'v'-5:'v'-0.289-6.4175.8381







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group70.6890.681
95

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 0.689 & 0.681 \tabularnewline
  & 95 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298083&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]7[/C][C]0.689[/C][C]0.681[/C][/ROW]
[ROW][C] [/C][C]95[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298083&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298083&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
DfF valuePr(>F)
Group70.6890.681
95



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):
par4 <- 'TRUE'
par3 <- '3'
par2 <- '2'
par1 <- '1'
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')