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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 computationMon, 15 Dec 2014 13:46:53 +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/15/t1418651279bbpsvz91qwnfxsf.htm/, Retrieved Thu, 31 Oct 2024 23:44:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268389, Retrieved Thu, 31 Oct 2024 23:44:19 +0000
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Estimated Impact117
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-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA (Gend...] [2014-12-15 13:46:53] [3bdd9332f2b4587684e97c4d9c2e2a73] [Current]
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Dataseries X:
26	0
37	0
67	1
43	1
52	1
52	0
43	1
84	1
67	1
49	1
70	1
52	1
58	0
68	0
62	0
43	1
56	0
56	1
74	0
65	1
63	1
58	0
57	1
63	1
53	1
57	1
51	0
64	1
53	0
29	0
54	0
58	1
51	1
53	1
54	0
56	1
61	1
47	0
39	1
48	1
50	1
35	1
30	1
68	0
49	1
61	1
67	0
47	1
56	1
50	1
43	1
67	1
62	1
57	1
41	0
54	1
45	0
48	1
61	1
56	0
41	0
43	1
53	0
44	1
66	0
58	1
46	1
37	0
51	0
51	0
56	0
66	1
37	0
38	1
66	0
34	0
53	1
49	0
55	0
49	0
59	1
40	0
58	1
60	1
63	0
56	0
54	0
52	1
34	1
69	1
32	0
48	1
67	0
58	1
57	1
42	1
64	1
58	1
66	0
26	1
61	1
52	1
51	0
55	0
50	0
60	0
56	0
63	0
61	1
52	1
16	1
46	1
56	1
52	0
55	1
50	1
59	0
60	1
52	0
44	0
67	1
52	1
55	1
37	1
54	1
72	1
51	1
48	1
60	0
50	1
63	1
33	1
67	1
46	1
54	1
59	0
61	1
33	1
47	1
69	1
52	1
55	0
41	0
73	1
52	0
50	0
51	1
60	0
56	1
56	1
29	0
66	1
66	1
73	1
55	0
64	0
40	0
46	0
58	1
43	0
61	1
51	0
50	1
52	0
54	1
66	0
61	0
80	1
51	0
56	1
56	1
56	1
53	1
47	1
25	0
47	1
46	0
50	0
39	0
51	1
58	0
35	1
58	0
60	0
62	0
63	0
53	1
46	1
67	1
59	1
64	0
38	0
50	1
48	0
48	0
47	0
66	0
47	1
63	1
58	0
44	0
51	1
43	0
55	1
38	1
45	0
50	1
54	1
57	1
60	0
55	0
56	0
49	1
37	1
59	1
46	1
51	0
58	0
64	0
53	1
48	1
51	0
47	0
59	0
62	1
62	1
51	0
64	0
52	0
67	1
50	1
54	1
58	1
56	0
63	1
31	1
65	1
71	0
50	0
57	1
47	0
47	1
57	1
43	0
41	1
63	0
63	1
56	1
51	0
50	1
22	0
41	1
59	0
56	1
66	0
53	0
42	1
52	1
54	0
44	1
62	1
53	0
50	1
36	0
76	0
66	1
62	1
59	0
47	1
55	0
58	0
60	1
44	0
57	0
45	1
58	1
51	1
57	0
30	1
46	1
51	1
56	1
58	0
44	1
14	0
53	0
42	1
49	0
44	1
62	0
30	0
46	1
56	0
50	1
54	1
48	0
55	0
35	0
55	1
41	0
59	1
54	1
66	1
55	1
45	0
51	1
47	0
42	1
53	0
53	0
41	0
55	0
55	0
46	0
63	1
43	1
65	1
59	0
39	0
44	0
60	0
57	0
67	1
52	1
52	1
69	1
46	0
46	1
53	0
40	1
70	1
54	0
77	1
45	0
60	0
47	0
50	0
66	0
60	0
41	1
53	0
34	0
51	1
69	1
60	1
45	1
58	0
39	1
51	1
52	0
49	0
63	0
44	0
51	1
52	0
60	0
53	0
53	0
52	0
31	0
51	1
65	1
51	1
49	0
61	0
58	1
62	0
54	1
52	1
72	1
50	1
65	1
53	0
56	0
63	0
62	0
66	0
50	1
45	0
58	0
52	1
53	0
68	0
59	1
58	0
52	1
45	1
58	0
70	1
69	0
71	1
46	0
58	1
39	1
46	1
64	0
67	1
44	1
54	0
41	1
68	1
63	1
57	1
61	0
39	1
69	0
64	0
38	1
59	0
51	1
59	1
51	0
65	0
47	1
50	1
57	1
21	1
47	0
51	1
37	1
67	1
43	1
58	0
51	0
40	1
41	0
58	1
64	1
64	0
58	1
50	0
59	1
55	0
59	0
58	1
41	1
56	1
63	1
77	0
60	0
58	1
64	0
47	1
46	0
62	1
60	1
50	1
46	1
44	1
58	1
56	1
43	1
54	0
54	1
56	0
65	0
66	1
62	1
58	1
67	1
25	1
56	1
53	1
56	0
59	1
46	1
49	1
56	0
76	1
33	1
49	1
53	1
58	0
72	1
51	1
42	0
69	0
51	1
54	1
52	1
59	1
51	0
67	1
64	0
58	1
53	1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268389&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268389&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268389&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







ANOVA Model
I ~ G
means53.1270.46

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
I  ~  G \tabularnewline
means & 53.127 & 0.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268389&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]I  ~  G[/C][/ROW]
[ROW][C]means[/C][C]53.127[/C][C]0.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268389&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268389&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
I ~ G
means53.1270.46







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
G125.31725.3170.2430.622
Residuals48450323.959103.975

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
G & 1 & 25.317 & 25.317 & 0.243 & 0.622 \tabularnewline
Residuals & 484 & 50323.959 & 103.975 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268389&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]G[/C][C]1[/C][C]25.317[/C][C]25.317[/C][C]0.243[/C][C]0.622[/C][/ROW]
[ROW][C]Residuals[/C][C]484[/C][C]50323.959[/C][C]103.975[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268389&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268389&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)
G125.31725.3170.2430.622
Residuals48450323.959103.975







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.46-1.3722.2930.622

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.46 & -1.372 & 2.293 & 0.622 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268389&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]1-0[/C][C]0.46[/C][C]-1.372[/C][C]2.293[/C][C]0.622[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268389&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268389&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
1-00.46-1.3722.2930.622







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.3180.573
484

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.318 & 0.573 \tabularnewline
  & 484 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268389&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]1[/C][C]0.318[/C][C]0.573[/C][/ROW]
[ROW][C] [/C][C]484[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268389&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268389&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)
Group10.3180.573
484



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){
'Tukey Plot'
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<-leveneTest(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')