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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, 11 Dec 2014 22:14:27 +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/11/t1418336079f8zlisqkq4uydgb.htm/, Retrieved Thu, 31 Oct 2024 23:25:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266385, Retrieved Thu, 31 Oct 2024 23:25:44 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-11 22:14:27] [478aede7ebf40ce01402b5cfefb74b76] [Current]
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Dataseries X:
50 1
62 1
54 1
71 1
54 1
65 1
73 1
52 1
84 1
42 1
66 1
65 1
78 1
73 1
75 1
72 0
66 1
70 1
61 0
81 1
71 1
69 1
71 1
72 1
68 1
70 1
68 0
61 0
67 1
76 1
70 1
60 1
72 1
69 1
71 1
62 1
70 1
64 0
58 1
76 1
52 1
59 1
68 1
76 1
65 0
67 1
59 1
69 0
76 1
63 0
75 0
63 0
60 1
73 0
63 1
70 1
75 0
66 1
63 0
63 0
64 1
70 1
75 1
61 1
60 1
62 0
73 1
61 1
66 1
64 0
59 1
64 1
60 0
56 0
78 1
53 1
67 1
59 0
66 1
68 0
71 1
66 0
73 0
72 0
71 0
59 0
64 0
66 0
78 0
68 0
73 0
62 0
65 0
68 0
65 0
60 0
71 0
65 0
68 0
64 0
74 0
69 0
76 0
68 0
72 0
67 0
63 0
59 0
73 0
66 0
62 0
69 0
66 0
51 1
56 1
67 1
69 1
57 0
56 0
55 1
63 1
67 1
65 1
47 1
76 1
64 1
68 1
64 1
65 1
71 0
63 1
60 1
68 1
72 1
70 1
61 1
61 1
62 1
71 1
71 1
51 1
56 0
70 1
73 1
76 1
68 1
48 1
52 1
60 1
59 1
57 1
79 1
60 1
60 1
59 1
62 0
59 0
61 1
71 1
57 0
66 0
63 0
69 0
58 1
59 1
48 0
66 0
73 0
67 0
61 0
68 0
75 0
62 0
69 0
58 1
60 1
74 0
55 1
62 1
63 0
69 1
58 0
58 0
68 1
72 0
62 0
62 0
65 0
69 0
66 0
72 0
62 0
75 0
58 0
66 0
55 0
47 0
72 1
62 0
64 0
64 0
19 1
50 0
68 1
70 0
79 1
69 0
71 1
48 0
73 0
74 0
66 0
71 1
74 1
78 0
75 1
53 1
60 0
70 1
69 0
65 0
78 1
78 0
59 1
72 1
70 1
63 0
63 1
71 0
74 1
67 1
66 1
62 1
80 0
73 1
67 1
61 1
73 0
74 1
32 1
69 0
69 1
84 0
64 0
58 0
59 0
78 0
57 1
60 1
68 1
68 1
73 1
69 1
67 0
60 0
65 1
66 0
74 0
81 1
72 0
55 0
49 0
74 0
53 0
64 0
65 0
57 0
51 0
80 0
67 0
70 0
74 0
75 0
70 0
69 0
65 0
55 1
71 0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266385&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266385&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266385&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'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
AMS.E ~ B_S
means65.867-0.685

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
AMS.E  ~  B_S \tabularnewline
means & 65.867 & -0.685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266385&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]AMS.E  ~  B_S[/C][/ROW]
[ROW][C]means[/C][C]65.867[/C][C]-0.685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266385&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266385&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
AMS.E ~ B_S
means65.867-0.685







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
B_S132.5732.570.4850.487
Residuals27618522.87367.112

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
B_S & 1 & 32.57 & 32.57 & 0.485 & 0.487 \tabularnewline
Residuals & 276 & 18522.873 & 67.112 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266385&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]B_S[/C][C]1[/C][C]32.57[/C][C]32.57[/C][C]0.485[/C][C]0.487[/C][/ROW]
[ROW][C]Residuals[/C][C]276[/C][C]18522.873[/C][C]67.112[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266385&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266385&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)
B_S132.5732.570.4850.487
Residuals27618522.87367.112







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-0.685-2.621.250.487

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -0.685 & -2.62 & 1.25 & 0.487 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266385&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]-0.685[/C][C]-2.62[/C][C]1.25[/C][C]0.487[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266385&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266385&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
1-0-0.685-2.621.250.487







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group13.2480.073
276

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 3.248 & 0.073 \tabularnewline
  & 276 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266385&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]3.248[/C][C]0.073[/C][/ROW]
[ROW][C] [/C][C]276[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266385&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266385&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)
Group13.2480.073
276



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')