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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 22:41:57 +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/t148192639867sfzaooj8inl4c.htm/, Retrieved Thu, 02 May 2024 18:29:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300574, Retrieved Thu, 02 May 2024 18:29:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72

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)] [1-way ANOVA] [2016-12-16 21:41:57] [16f5b9a58ec3c52886915d5c1a5d203e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3	5
4	2
4	3
3	3
3	3
4	4
3	4
3	2
3	5
3	4
4	2
3	4
5	3
4	3
4	4
3	2
5	1
NA	NA
2	2
2	3
3	5
3	4
3	5
3	3
4	5
4	2
4	4
4	4
2	3
4	2
3	1
3	2
4	5
2	4
4	3
4	2
3	1
3	3
4	3
3	3
4	5
3	2
3	2
4	1
4	4
3	4
3	2
3	1
3	5
1	4
3	4
4	4
4	2
2	2
4	3
4	2
3	3
5	4
3	3
2	2
3	2
4	1
3	3
3	4
4	4
3	4
4	3
3	5
5	4
4	1
4	1
4	5
2	5
3	3
5	2
4	4
4	4
4	4
4	4
3	5
NA	4
4	4
4	4
4	2
3	1
4	1
3	5
3	5
3	3
4	2
3	4
3	2
3	3
3	1
3	5
4	4
3	2
3	2
NA	1
3	4
3	2
4	3
4	1
4	2
4	3
4	1
NA	5
4	4
4	1
3	4
3	1
3	4
3	2
4	3
3	3
3	3
4	3
3	3
3	2
4	2
3	4
3	2
3	5
3	1
NA	3
4	3
3	3
4	4
4	3
3	3
3	2
4	4
3	5
4	4
4	4
NA	4
5	3
NA	4
4	3
4	NA
3	1
3	2
3	1
4	4
4	5
3	4
3	3
3	2
3	1
3	3
4	4
4	4
3	1
2	5
2	3
3	NA
3	4
4	1
3	3
4	3
2	4
4	4
3	5
3	1
3	NA
3	1
3	5
3	3
4	4

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=300574&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=300574&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300574&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
GW4 ~ EC1
means3.478-0.166-0.0940.067-0.335-0.145

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
GW4  ~  EC1 \tabularnewline
means & 3.478 & -0.166 & -0.094 & 0.067 & -0.335 & -0.145 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300574&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]GW4  ~  EC1[/C][/ROW]
[ROW][C]means[/C][C]3.478[/C][C]-0.166[/C][C]-0.094[/C][C]0.067[/C][C]-0.335[/C][C]-0.145[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300574&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300574&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
GW4 ~ EC1
means3.478-0.166-0.0940.067-0.335-0.145






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
EC152.7240.5451.1490.337
Residuals15673.9920.474 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
EC1 & 5 & 2.724 & 0.545 & 1.149 & 0.337 \tabularnewline
Residuals & 156 & 73.992 & 0.474 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300574&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]EC1[/C][C]5[/C][C]2.724[/C][C]0.545[/C][C]1.149[/C][C]0.337[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]73.992[/C][C]0.474[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300574&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300574&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)
EC152.7240.5451.1490.337
Residuals15673.9920.474






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-1-0.166-0.7090.3770.951
3-1-0.094-0.6160.4290.995
4-10.067-0.4440.5790.999
5-1-0.335-0.9350.2640.591
NA-1-0.145-1.3651.0750.999
3-20.072-0.4020.5460.998
4-20.233-0.2290.6950.693
5-2-0.17-0.7280.3880.951
NA-20.021-1.1791.2211
4-30.161-0.2760.5980.896
5-3-0.242-0.780.2960.786
NA-3-0.051-1.2421.1391
5-4-0.403-0.930.1240.242
NA-4-0.212-1.3980.9740.995
NA-50.19-1.0361.4170.998

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & -0.166 & -0.709 & 0.377 & 0.951 \tabularnewline
3-1 & -0.094 & -0.616 & 0.429 & 0.995 \tabularnewline
4-1 & 0.067 & -0.444 & 0.579 & 0.999 \tabularnewline
5-1 & -0.335 & -0.935 & 0.264 & 0.591 \tabularnewline
NA-1 & -0.145 & -1.365 & 1.075 & 0.999 \tabularnewline
3-2 & 0.072 & -0.402 & 0.546 & 0.998 \tabularnewline
4-2 & 0.233 & -0.229 & 0.695 & 0.693 \tabularnewline
5-2 & -0.17 & -0.728 & 0.388 & 0.951 \tabularnewline
NA-2 & 0.021 & -1.179 & 1.221 & 1 \tabularnewline
4-3 & 0.161 & -0.276 & 0.598 & 0.896 \tabularnewline
5-3 & -0.242 & -0.78 & 0.296 & 0.786 \tabularnewline
NA-3 & -0.051 & -1.242 & 1.139 & 1 \tabularnewline
5-4 & -0.403 & -0.93 & 0.124 & 0.242 \tabularnewline
NA-4 & -0.212 & -1.398 & 0.974 & 0.995 \tabularnewline
NA-5 & 0.19 & -1.036 & 1.417 & 0.998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300574&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]-0.166[/C][C]-0.709[/C][C]0.377[/C][C]0.951[/C][/ROW]
[ROW][C]3-1[/C][C]-0.094[/C][C]-0.616[/C][C]0.429[/C][C]0.995[/C][/ROW]
[ROW][C]4-1[/C][C]0.067[/C][C]-0.444[/C][C]0.579[/C][C]0.999[/C][/ROW]
[ROW][C]5-1[/C][C]-0.335[/C][C]-0.935[/C][C]0.264[/C][C]0.591[/C][/ROW]
[ROW][C]NA-1[/C][C]-0.145[/C][C]-1.365[/C][C]1.075[/C][C]0.999[/C][/ROW]
[ROW][C]3-2[/C][C]0.072[/C][C]-0.402[/C][C]0.546[/C][C]0.998[/C][/ROW]
[ROW][C]4-2[/C][C]0.233[/C][C]-0.229[/C][C]0.695[/C][C]0.693[/C][/ROW]
[ROW][C]5-2[/C][C]-0.17[/C][C]-0.728[/C][C]0.388[/C][C]0.951[/C][/ROW]
[ROW][C]NA-2[/C][C]0.021[/C][C]-1.179[/C][C]1.221[/C][C]1[/C][/ROW]
[ROW][C]4-3[/C][C]0.161[/C][C]-0.276[/C][C]0.598[/C][C]0.896[/C][/ROW]
[ROW][C]5-3[/C][C]-0.242[/C][C]-0.78[/C][C]0.296[/C][C]0.786[/C][/ROW]
[ROW][C]NA-3[/C][C]-0.051[/C][C]-1.242[/C][C]1.139[/C][C]1[/C][/ROW]
[ROW][C]5-4[/C][C]-0.403[/C][C]-0.93[/C][C]0.124[/C][C]0.242[/C][/ROW]
[ROW][C]NA-4[/C][C]-0.212[/C][C]-1.398[/C][C]0.974[/C][C]0.995[/C][/ROW]
[ROW][C]NA-5[/C][C]0.19[/C][C]-1.036[/C][C]1.417[/C][C]0.998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300574&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300574&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
2-1-0.166-0.7090.3770.951
3-1-0.094-0.6160.4290.995
4-10.067-0.4440.5790.999
5-1-0.335-0.9350.2640.591
NA-1-0.145-1.3651.0750.999
3-20.072-0.4020.5460.998
4-20.233-0.2290.6950.693
5-2-0.17-0.7280.3880.951
NA-20.021-1.1791.2211
4-30.161-0.2760.5980.896
5-3-0.242-0.780.2960.786
NA-3-0.051-1.2421.1391
5-4-0.403-0.930.1240.242
NA-4-0.212-1.3980.9740.995
NA-50.19-1.0361.4170.998






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group50.4440.817
156 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 0.444 & 0.817 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300574&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]5[/C][C]0.444[/C][C]0.817[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300574&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300574&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)
Group50.4440.817
156


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 <- '2'
par1 <- '1'
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')