Free Statistics

of Irreproducible Research!

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 computationFri, 12 Dec 2014 12:17:44 +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/Dec/12/t14183866994midmonpe3w444y.htm/, Retrieved Thu, 16 May 2024 20:35:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266591, Retrieved Thu, 16 May 2024 20:35:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [] [2014-12-12 12:17:44] [25032714cc1544fa8afe1ed03205f94e] [Current]
- R P     [Two-Way ANOVA] [Two way anova mot...] [2014-12-17 13:09:05] [67894a4ff6098ffac356bc81e6028257]
- R P     [Two-Way ANOVA] [] [2014-12-17 13:13:12] [67894a4ff6098ffac356bc81e6028257]
Feedback Forum

Post a new message
Dataseries X:
26 0 2011
51 0 2011
57 0 2011
37 0 2011
67 0 2011
43 0 2011
52 0 2011
52 0 2011
43 0 2011
84 0 2011
67 0 2011
49 0 2011
70 0 2011
52 0 2011
58 0 2011
68 0 2011
62 1 2011
43 0 2011
56 0 2011
56 1 2011
74 0 2011
65 0 2011
63 0 2011
58 0 2011
57 0 2011
63 0 2011
53 0 2011
57 1 2011
51 1 2011
64 0 2011
53 0 2011
29 0 2011
54 0 2011
51 0 2011
58 0 2011
43 0 2011
51 0 2011
53 0 2011
54 0 2011
56 1 2011
61 0 2011
47 0 2011
39 0 2011
48 0 2011
50 0 2011
35 0 2011
30 1 2011
68 0 2011
49 0 2011
61 1 2011
67 0 2011
47 1 2011
56 1 2011
50 1 2011
43 0 2011
67 1 2011
62 0 2011
57 0 2011
41 1 2011
54 0 2011
45 1 2011
48 1 2011
61 0 2011
56 0 2011
41 0 2011
43 0 2011
53 0 2011
44 1 2011
66 0 2011
58 0 2011
46 0 2011
37 1 2011
51 0 2011
51 0 2011
56 1 2011
66 1 2011
45 0 2011
37 0 2011
59 0 2011
42 0 2011
38 1 2011
66 0 2011
34 1 2011
53 0 2011
49 1 2011
55 1 2011
49 1 2011
59 1 2011
40 1 2011
58 1 2011
60 1 2011
63 1 2011
56 1 2011
54 1 2011
52 1 2011
34 1 2011
69 1 2011
32 1 2011
48 1 2011
67 1 2011
58 1 2011
57 1 2011
42 1 2011
64 1 2011
58 1 2011
66 1 2011
26 1 2011
61 1 2011
52 1 2011
51 1 2011
55 1 2011
50 1 2011
60 1 2011
56 1 2011
63 1 2011
61 1 2011
52 0 2012
16 0 2012
46 0 2012
56 0 2012
52 1 2012
55 1 2012
50 0 2012
59 0 2012
60 0 2012
52 0 2012
44 0 2012
67 0 2012
52 0 2012
55 0 2012
37 0 2012
54 0 2012
72 1 2012
51 0 2012
48 0 2012
60 0 2012
50 0 2012
63 0 2012
33 0 2012
67 0 2012
46 0 2012
54 0 2012
59 0 2012
61 0 2012
33 1 2012
47 0 2012
69 0 2012
52 0 2012
55 0 2012
55 0 2012
41 0 2012
73 0 2012
51 0 2012
52 0 2012
50 0 2012
51 0 2012
60 0 2012
56 0 2012
56 0 2012
29 0 2012
66 1 2012
66 1 2012
73 0 2012
55 0 2012
64 1 2012
40 1 2012
46 1 2012
58 1 2012
43 0 2012
61 0 2012
51 1 2012
50 1 2012
52 1 2012
54 1 2012
66 1 2012
61 1 2012
80 1 2012
51 1 2012
56 1 2012
56 0 2012
56 0 2012
53 1 2012
47 0 2012
25 0 2012
47 1 2012
46 0 2012
50 1 2012
39 1 2012
51 0 2012
58 1 2012
35 1 2012
58 1 2012
60 1 2012
62 1 2012
63 1 2012
53 1 2012
46 1 2012
67 1 2012
59 1 2012
64 1 2012
38 1 2012
50 1 2012
48 0 2012
48 1 2012
47 1 2012
66 1 2012
47 0 2012
63 1 2012
58 0 2012
44 1 2012
51 0 2012
43 1 2012
55 0 2012
38 1 2012
56 1 2012
45 1 2012
50 1 2012
54 1 2012
57 0 2012
60 0 2012
55 1 2012
56 0 2012
49 0 2012
37 1 2012
43 0 2012
59 0 2012
46 1 2012
51 1 2012
58 0 2012
64 1 2012
53 0 2012
48 0 2012
51 0 2012
47 1 2012
59 0 2012
62 1 2012
62 0 2012
51 0 2012
64 0 2012
52 0 2012
67 1 2012
50 0 2012
54 0 2012
58 0 2012
56 1 2012
63 0 2012
31 0 2012
65 1 2012
71 0 2012
50 1 2012
57 1 2012
47 1 2012
54 0 2012
47 1 2012
57 1 2012
43 0 2012
41 0 2012
63 0 2012
63 0 2012
56 0 2012
51 0 2012
50 1 2012
22 1 2012
41 0 2012
59 1 2012
56 1 2012
66 0 2012
53 1 2012
42 1 2012
52 1 2012
54 1 2012
44 1 2012
62 1 2012
53 1 2012
50 1 2012
36 1 2012
76 1 2012
66 1 2012
62 1 2012
59 1 2012
47 1 2012
55 1 2012
58 1 2012
60 1 2012
44 0 2012
57 1 2012
45 1 2012
58 0 2014
51 0 2014
57 0 2014
30 0 2014
46 0 2014
51 0 2014
56 0 2014
58 0 2014
44 0 2014
14 0 2014
53 0 2014
42 0 2014
49 1 2014
44 0 2014
62 1 2014
30 0 2014
46 0 2014
56 1 2014
50 0 2014
54 0 2014
48 0 2014
55 0 2014
35 0 2014
55 0 2014
41 0 2014
59 0 2014
54 0 2014
66 0 2014
55 0 2014
45 0 2014
51 0 2014
47 0 2014
42 0 2014
53 0 2014
53 0 2014
41 0 2014
55 0 2014
55 0 2014
46 0 2014
63 0 2014
43 0 2014
65 0 2014
59 0 2014
39 0 2014
44 0 2014
60 1 2014
57 0 2014
67 1 2014
52 1 2014
52 1 2014
69 0 2014
46 0 2014
46 0 2014
53 1 2014
40 0 2014
70 0 2014
54 0 2014
77 0 2014
45 1 2014
60 0 2014
47 1 2014
50 0 2014
66 0 2014
60 0 2014
41 1 2014
53 1 2014
34 1 2014
51 0 2014
69 0 2014
60 0 2014
45 1 2014
58 0 2014
39 0 2014
51 0 2014
52 0 2014
49 0 2014
63 0 2014
44 1 2014
51 0 2014
52 0 2014
60 1 2014
53 1 2014
53 1 2014
52 0 2014
31 0 2014
51 1 2014
65 1 2014
51 1 2014
49 1 2014
61 0 2014
58 1 2014
62 1 2014
54 0 2014
52 1 2014
72 0 2014
50 1 2014
65 0 2014
53 1 2014
56 0 2014
63 0 2014
62 1 2014
66 1 2014
50 1 2014
45 0 2014
58 1 2014
52 0 2014
53 1 2014
68 0 2014
59 1 2014
58 1 2014
52 1 2014
45 0 2014
58 1 2014
70 0 2014
69 0 2014
71 1 2014
46 0 2014
58 1 2014
39 0 2014
46 1 2014
64 1 2014
67 1 2014
44 1 2014
54 0 2014
41 0 2014
68 0 2014
63 0 2014
57 0 2014
61 0 2014
39 0 2014
69 1 2014
64 1 2014
38 1 2014
59 0 2014
51 0 2014
59 1 2014
51 0 2014
65 0 2014
47 1 2014
50 0 2014
57 1 2014
21 0 2014
47 0 2014
51 1 2014
37 0 2014
67 1 2014
43 1 2014
58 0 2014
51 0 2014
40 0 2014
41 1 2014
58 1 2014
64 1 2014
64 0 2014
58 0 2014
50 1 2014
59 1 2014
55 1 2014
59 1 2014
58 1 2014
41 1 2014
56 0 2014
63 0 2014
77 1 2014
60 0 2014
58 1 2014
64 0 2014
47 0 2014
46 0 2014
62 1 2014
60 1 2014
50 0 2014
46 0 2014
44 0 2014
58 0 2014
56 1 2014
43 1 2014
54 1 2014
54 1 2014
56 1 2014
65 1 2014
66 1 2014
62 1 2014
58 0 2014
67 1 2014
25 0 2014
56 0 2014
53 1 2014
56 0 2014
59 0 2014
46 0 2014
49 1 2014
56 1 2014
76 1 2014
33 1 2014
49 0 2014
53 0 2014
58 0 2014
72 1 2014
51 1 2014
42 1 2014
69 1 2014
51 1 2014
54 0 2014
52 0 2014
59 0 2014
51 1 2014
67 1 2014
64 1 2014
58 1 2014




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266591&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266591&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266591&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B - 1
means53.53152.442-0.834-1.2951.984.428

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B - 1 \tabularnewline
means & 53.531 & 52.442 & -0.834 & -1.295 & 1.98 & 4.428 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266591&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B - 1[/C][/ROW]
[ROW][C]means[/C][C]53.531[/C][C]52.442[/C][C]-0.834[/C][C]-1.295[/C][C]1.98[/C][C]4.428[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266591&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266591&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 - 1
means53.53152.442-0.834-1.2951.984.428







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A21413222.06706611.036916.1080
Treatment_B244.88322.4420.220.803
Treatment_A:Treatment_B2380.137190.0691.860.157
Residuals49150164.919102.169

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 1413222.06 & 706611.03 & 6916.108 & 0 \tabularnewline
Treatment_B & 2 & 44.883 & 22.442 & 0.22 & 0.803 \tabularnewline
Treatment_A:Treatment_B & 2 & 380.137 & 190.069 & 1.86 & 0.157 \tabularnewline
Residuals & 491 & 50164.919 & 102.169 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266591&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]2[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]2[/C][C]1413222.06[/C][C]706611.03[/C][C]6916.108[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]44.883[/C][C]22.442[/C][C]0.22[/C][C]0.803[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]380.137[/C][C]190.069[/C][C]1.86[/C][C]0.157[/C][/ROW]
[ROW][C]Residuals[/C][C]491[/C][C]50164.919[/C][C]102.169[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266591&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266591&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)
2
Treatment_A21413222.06706611.036916.1080
Treatment_B244.88322.4420.220.803
Treatment_A:Treatment_B2380.137190.0691.860.157
Residuals49150164.919102.169







Must Include Intercept to use Tukey Test

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266591&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266591&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266591&T=3

As an alternative you can also use a QR Code:  

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

Must Include Intercept to use Tukey Test







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group50.3760.865
491

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 0.376 & 0.865 \tabularnewline
  & 491 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266591&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]5[/C][C]0.376[/C][C]0.865[/C][/ROW]
[ROW][C] [/C][C]491[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266591&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266591&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)
Group50.3760.865
491



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = FALSE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = FALSE ;
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')