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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_One Factor ANOVA.wasp

Title produced by software

One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation

Fri, 16 Dec 2016 17:23:23 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/16/t1481905428cg3apwxift8b712.htm/, Retrieved Fri, 01 Nov 2024 03:28:07 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300421, Retrieved Fri, 01 Nov 2024 03:28:07 +0000

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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)] [One Way Anova] [2016-12-16 16:23:23] [6fe662842930c5949e61d44eeb8a265b] [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=300421&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=300421&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300421&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
TVDC3 ~ SKEOU2
means	3	0.818	1.241	1.636

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
TVDC3  ~  SKEOU2 \tabularnewline
means & 3 & 0.818 & 1.241 & 1.636 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300421&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]TVDC3  ~  SKEOU2[/C][/ROW]
[ROW][C]means[/C][C]3[/C][C]0.818[/C][C]1.241[/C][C]1.636[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300421&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300421&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
TVDC3 ~ SKEOU2
means	3	0.818	1.241	1.636

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
SKEOU2	3	13.346	4.449	13.793	0
Residuals	160	51.605	0.323

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
SKEOU2 & 3 & 13.346 & 4.449 & 13.793 & 0 \tabularnewline
Residuals & 160 & 51.605 & 0.323 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300421&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]SKEOU2[/C][C]3[/C][C]13.346[/C][C]4.449[/C][C]13.793[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]160[/C][C]51.605[/C][C]0.323[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300421&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300421&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)
SKEOU2	3	13.346	4.449	13.793	0
Residuals	160	51.605	0.323

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
3-2	0.818	0.017	1.62	0.043
4-2	1.241	0.492	1.991	0
5-2	1.636	0.835	2.438	0
4-3	0.423	0.08	0.766	0.009
5-3	0.818	0.374	1.263	0
5-4	0.395	0.052	0.738	0.017

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
3-2 & 0.818 & 0.017 & 1.62 & 0.043 \tabularnewline
4-2 & 1.241 & 0.492 & 1.991 & 0 \tabularnewline
5-2 & 1.636 & 0.835 & 2.438 & 0 \tabularnewline
4-3 & 0.423 & 0.08 & 0.766 & 0.009 \tabularnewline
5-3 & 0.818 & 0.374 & 1.263 & 0 \tabularnewline
5-4 & 0.395 & 0.052 & 0.738 & 0.017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300421&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]0.818[/C][C]0.017[/C][C]1.62[/C][C]0.043[/C][/ROW]
[ROW][C]4-2[/C][C]1.241[/C][C]0.492[/C][C]1.991[/C][C]0[/C][/ROW]
[ROW][C]5-2[/C][C]1.636[/C][C]0.835[/C][C]2.438[/C][C]0[/C][/ROW]
[ROW][C]4-3[/C][C]0.423[/C][C]0.08[/C][C]0.766[/C][C]0.009[/C][/ROW]
[ROW][C]5-3[/C][C]0.818[/C][C]0.374[/C][C]1.263[/C][C]0[/C][/ROW]
[ROW][C]5-4[/C][C]0.395[/C][C]0.052[/C][C]0.738[/C][C]0.017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300421&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300421&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
3-2	0.818	0.017	1.62	0.043
4-2	1.241	0.492	1.991	0
5-2	1.636	0.835	2.438	0
4-3	0.423	0.08	0.766	0.009
5-3	0.818	0.374	1.263	0
5-4	0.395	0.052	0.738	0.017

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	3	0.309	0.819
	160

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.309 & 0.819 \tabularnewline
  & 160 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300421&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]3[/C][C]0.309[/C][C]0.819[/C][/ROW]
[ROW][C] [/C][C]160[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300421&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300421&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	3	0.309	0.819
	160

Figure 1

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Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

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

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

par3 <- 'TRUE'
par2 <- '1'
par1 <- '2'
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code