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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 computationFri, 16 Dec 2016 23:25:57 +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/16/t1481927280h90k4ou5qgzlaek.htm/, Retrieved Fri, 03 May 2024 00:10:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300578, Retrieved Fri, 03 May 2024 00:10:30 +0000
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Estimated Impact80

Tree of Dependent Computations

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-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ONE WAY ITHSUM-kv...] [2016-12-16 22:25:57] [1e2c9196efc58119c3757b6c78ac7c5f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5	4	4	4	14
5	4	4	4	19
4	3	3	2	17
4	3	3	3	17
5	4	4	3	15
5	3	4	3	20
5	4	2	3	15
5	4	2	4	19
5	2	2	4	15
5	1	2	4	15
4	4	3	2	19
5	4	3	2	16
5	4	5	4	20
5	5	4	5	18
4	4	3	4	15
5	1	4	4	14
3	4	4	2	20
5	2	2	2	16
5	3	4	5	16
5	3	4	4	16
2	2	3	1	10
3	1	3	5	19
4	3	2	3	19
4	2	2	4	16
4	3	3	4	15
5	4	3	2	18
4	4	3	4	17
5	2	4	2	19
4	3	4	3	17
5	4	3	4	14
4	4	4	4	19
4	4	3	4	20
4	3	4	4	5
5	4	3	4	19
5	4	3	4	16
5	4	3	5	15
5	4	3	4	16
2	3	2	4	18
4	3	5	3	16
4	4	3	4	15
4	2	1	4	17
5	3	2	3	14
5	4	2	2	20
5	4	3	5	19
4	3	2	4	7
4	2	3	3	13
5	3	5	4	16
5	3	4	4	16
5	4	5	4	16
4	3	2	3	18
4	3	4	4	18
5	3	3	4	16
5	3	3	4	17
5	3	2	4	19
4	5	3	5	16
5	4	2	4	19
5	4	4	2	13
4	3	4	4	16
4	4	3	5	13
5	4	1	2	12
5	1	1	3	17
4	4	3	4	17
4	3	3	3	17
5	3	2	4	16
3	4	3	4	16
3	2	4	4	14
5	4	3	5	16
4	5	4	3	13
4	4	4	4	16
5	4	3	4	14
5	4	4	4	20
4	4	4	4	12
5	4	3	4	13
4	2	3	4	18
4	4	5	4	14
4	2	2	4	19
5	5	4	4	18
4	5	3	3	14
4	2	3	3	18
4	4	3	2	19
4	3	4	2	15
4	3	4	2	14
2	3	3	3	17
4	4	5	4	19
4	4	3	4	13
5	3	4	4	19
4	3	3	4	18
5	4	5	4	20
4	4	4	4	15
4	2	4	4	15
3	3	4	2	15
4	3	4	3	20
2	3	2	2	15
4	4	3	3	19
5	4	4	4	18
3	4	3	5	18
4	4	3	4	15
5	5	5	5	20
2	4	3	3	17
5	3	1	5	12
5	4	3	4	18
5	4	4	5	19
4	2	2	2	20
4	3	3	3	13
5	3	4	4	17
5	3	4	5	15
4	4	4	4	16
4	4	4	5	18
5	4	5	5	18
5	4	4	5	14
5	3	3	4	15
4	3	3	4	12
5	3	3	4	17
4	2	4	4	14
5	3	4	4	18
4	2	2	4	17
5	4	5	5	17
5	5	2	5	20
4	3	2	5	16
4	3	2	4	14
4	3	3	4	15
5	2	3	4	18
5	3	4	5	20
4	3	4	4	17
4	3	4	4	17
5	4	3	4	17
5	4	4	4	17
4	3	4	2	15
4	4	3	4	17
4	1	3	2	18
4	5	5	4	17
5	4	4	3	20
5	3	3	5	15
4	5	3	2	16
4	4	3	4	15
4	3	3	3	18
4	4	4	4	11
3	4	3	3	15
4	4	2	4	18
5	3	4	5	20
4	2	4	3	19
4	4	4	2	14
5	3	5	5	16
3	3	2	4	15
4	4	2	4	17
1	2	3	2	18
5	3	3	5	20
4	4	2	3	17
5	4	4	3	18
3	3	2	3	15
4	4	3	4	16
4	4	4	4	11
4	3	3	4	15
4	2	3	4	18
5	4	4	4	17
5	2	2	4	16
5	3	5	5	12
5	4	4	3	19
4	3	3	3	18
5	2	5	4	15
5	4	2	4	17
4	1	4	5	19
3	5	4	3	18
4	4	4	4	19
4	3	3	2	16
5	4	5	5	16
4	4	3	4	16
4	3	3	3	14

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300578&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=300578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300578&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 time4 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
KVDD1 ~ KVDD2
means4.333-0.333-0.0920.105-0.033

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
KVDD1  ~  KVDD2 \tabularnewline
means & 4.333 & -0.333 & -0.092 & 0.105 & -0.033 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300578&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]KVDD1  ~  KVDD2[/C][/ROW]
[ROW][C]means[/C][C]4.333[/C][C]-0.333[/C][C]-0.092[/C][C]0.105[/C][C]-0.033[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300578&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
KVDD1 ~ KVDD2
means4.333-0.333-0.0920.105-0.033






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
KVDD243.4910.8731.5130.201
Residuals16394.0270.577 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
KVDD2 & 4 & 3.491 & 0.873 & 1.513 & 0.201 \tabularnewline
Residuals & 163 & 94.027 & 0.577 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300578&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]KVDD2[/C][C]4[/C][C]3.491[/C][C]0.873[/C][C]1.513[/C][C]0.201[/C][/ROW]
[ROW][C]Residuals[/C][C]163[/C][C]94.027[/C][C]0.577[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300578&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300578&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)
KVDD243.4910.8731.5130.201
Residuals16394.0270.577






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-1-0.333-1.3030.6370.878
3-1-0.092-0.990.8070.999
4-10.105-0.7850.9950.998
5-1-0.033-1.1151.0491
3-20.241-0.2920.7750.723
4-20.438-0.080.9570.14
5-20.3-0.5051.1050.842
4-30.197-0.1720.5660.581
5-30.059-0.6590.7760.999
5-4-0.138-0.8450.5680.983

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & -0.333 & -1.303 & 0.637 & 0.878 \tabularnewline
3-1 & -0.092 & -0.99 & 0.807 & 0.999 \tabularnewline
4-1 & 0.105 & -0.785 & 0.995 & 0.998 \tabularnewline
5-1 & -0.033 & -1.115 & 1.049 & 1 \tabularnewline
3-2 & 0.241 & -0.292 & 0.775 & 0.723 \tabularnewline
4-2 & 0.438 & -0.08 & 0.957 & 0.14 \tabularnewline
5-2 & 0.3 & -0.505 & 1.105 & 0.842 \tabularnewline
4-3 & 0.197 & -0.172 & 0.566 & 0.581 \tabularnewline
5-3 & 0.059 & -0.659 & 0.776 & 0.999 \tabularnewline
5-4 & -0.138 & -0.845 & 0.568 & 0.983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300578&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]2-1[/C][C]-0.333[/C][C]-1.303[/C][C]0.637[/C][C]0.878[/C][/ROW]
[ROW][C]3-1[/C][C]-0.092[/C][C]-0.99[/C][C]0.807[/C][C]0.999[/C][/ROW]
[ROW][C]4-1[/C][C]0.105[/C][C]-0.785[/C][C]0.995[/C][C]0.998[/C][/ROW]
[ROW][C]5-1[/C][C]-0.033[/C][C]-1.115[/C][C]1.049[/C][C]1[/C][/ROW]
[ROW][C]3-2[/C][C]0.241[/C][C]-0.292[/C][C]0.775[/C][C]0.723[/C][/ROW]
[ROW][C]4-2[/C][C]0.438[/C][C]-0.08[/C][C]0.957[/C][C]0.14[/C][/ROW]
[ROW][C]5-2[/C][C]0.3[/C][C]-0.505[/C][C]1.105[/C][C]0.842[/C][/ROW]
[ROW][C]4-3[/C][C]0.197[/C][C]-0.172[/C][C]0.566[/C][C]0.581[/C][/ROW]
[ROW][C]5-3[/C][C]0.059[/C][C]-0.659[/C][C]0.776[/C][C]0.999[/C][/ROW]
[ROW][C]5-4[/C][C]-0.138[/C][C]-0.845[/C][C]0.568[/C][C]0.983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300578&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300578&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
2-1-0.333-1.3030.6370.878
3-1-0.092-0.990.8070.999
4-10.105-0.7850.9950.998
5-1-0.033-1.1151.0491
3-20.241-0.2920.7750.723
4-20.438-0.080.9570.14
5-20.3-0.5051.1050.842
4-30.197-0.1720.5660.581
5-30.059-0.6590.7760.999
5-4-0.138-0.8450.5680.983






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group40.0660.992
163 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 0.066 & 0.992 \tabularnewline
  & 163 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300578&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]0.066[/C][C]0.992[/C][/ROW]
[ROW][C] [/C][C]163[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300578&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300578&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)
Group40.0660.992
163


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 111111 ; par2 = 222222 ; par3 = TRUETRUETRUEFALSETRUETRUE ;
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')