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Description of Statistical Computation

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, 15 Dec 2016 11:09:50 +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/15/t1481796708s2zw6rbtzo8xlea.htm/, Retrieved Fri, 03 May 2024 07:47:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299812, Retrieved Fri, 03 May 2024 07:47:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75

Tree of Dependent Computations

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 blauw en ...] [2016-12-15 10:09:50] [e6dc02234f5305f92311fb16bc25f73e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1
4	1
6	0
1	6
8	3
3	3
8	2
7	1
7	3
4	1
6	0
2	3
5	1
2	2
5	1

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299812&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299812&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299812&T=0

As an alternative you can also use a QR Code:  
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 time3 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
Blauw ~ Groen
means6-1.667-1-1-5

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Blauw  ~  Groen \tabularnewline
means & 6 & -1.667 & -1 & -1 & -5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299812&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Blauw  ~  Groen[/C][/ROW]
[ROW][C]means[/C][C]6[/C][C]-1.667[/C][C]-1[/C][C]-1[/C][C]-5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299812&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299812&T=1

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Model
Blauw ~ Groen
means6-1.667-1-1-5






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Groen418.2674.5670.7210.597
Residuals1063.3336.333 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Groen & 4 & 18.267 & 4.567 & 0.721 & 0.597 \tabularnewline
Residuals & 10 & 63.333 & 6.333 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299812&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]Groen[/C][C]4[/C][C]18.267[/C][C]4.567[/C][C]0.721[/C][C]0.597[/C][/ROW]
[ROW][C]Residuals[/C][C]10[/C][C]63.333[/C][C]6.333[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299812&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299812&T=2

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Groen418.2674.5670.7210.597
Residuals1063.3336.333






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-1.667-8.4295.0960.921
2-0-1-9.2827.2820.994
3-0-1-8.1736.1730.989
6-0-5-15.1445.1440.517
2-10.667-6.0967.4290.997
3-10.667-4.686.0130.993
6-1-3.333-12.2795.6130.738
3-20-7.1737.1731
6-2-4-14.1446.1440.699
6-3-4-13.265.260.629

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -1.667 & -8.429 & 5.096 & 0.921 \tabularnewline
2-0 & -1 & -9.282 & 7.282 & 0.994 \tabularnewline
3-0 & -1 & -8.173 & 6.173 & 0.989 \tabularnewline
6-0 & -5 & -15.144 & 5.144 & 0.517 \tabularnewline
2-1 & 0.667 & -6.096 & 7.429 & 0.997 \tabularnewline
3-1 & 0.667 & -4.68 & 6.013 & 0.993 \tabularnewline
6-1 & -3.333 & -12.279 & 5.613 & 0.738 \tabularnewline
3-2 & 0 & -7.173 & 7.173 & 1 \tabularnewline
6-2 & -4 & -14.144 & 6.144 & 0.699 \tabularnewline
6-3 & -4 & -13.26 & 5.26 & 0.629 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299812&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]-1.667[/C][C]-8.429[/C][C]5.096[/C][C]0.921[/C][/ROW]
[ROW][C]2-0[/C][C]-1[/C][C]-9.282[/C][C]7.282[/C][C]0.994[/C][/ROW]
[ROW][C]3-0[/C][C]-1[/C][C]-8.173[/C][C]6.173[/C][C]0.989[/C][/ROW]
[ROW][C]6-0[/C][C]-5[/C][C]-15.144[/C][C]5.144[/C][C]0.517[/C][/ROW]
[ROW][C]2-1[/C][C]0.667[/C][C]-6.096[/C][C]7.429[/C][C]0.997[/C][/ROW]
[ROW][C]3-1[/C][C]0.667[/C][C]-4.68[/C][C]6.013[/C][C]0.993[/C][/ROW]
[ROW][C]6-1[/C][C]-3.333[/C][C]-12.279[/C][C]5.613[/C][C]0.738[/C][/ROW]
[ROW][C]3-2[/C][C]0[/C][C]-7.173[/C][C]7.173[/C][C]1[/C][/ROW]
[ROW][C]6-2[/C][C]-4[/C][C]-14.144[/C][C]6.144[/C][C]0.699[/C][/ROW]
[ROW][C]6-3[/C][C]-4[/C][C]-13.26[/C][C]5.26[/C][C]0.629[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299812&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299812&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-1.667-8.4295.0960.921
2-0-1-9.2827.2820.994
3-0-1-8.1736.1730.989
6-0-5-15.1445.1440.517
2-10.667-6.0967.4290.997
3-10.667-4.686.0130.993
6-1-3.333-12.2795.6130.738
3-20-7.1737.1731
6-2-4-14.1446.1440.699
6-3-4-13.265.260.629






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group43.8810.037
10 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 3.881 & 0.037 \tabularnewline
  & 10 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299812&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]4[/C][C]3.881[/C][C]0.037[/C][/ROW]
[ROW][C] [/C][C]10[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299812&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299812&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group43.8810.037
10


Figures (Output of Computation)

Input Parameters & R Code

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):
par3 <- 'TRUE'
par2 <- ''
par1 <- ''
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')