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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationThu, 11 Jun 2020 02:35:27 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Jun/11/t1591835840ehlzfy4clt0nuwy.htm/, Retrieved Sat, 18 May 2024 19:01:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319172, Retrieved Sat, 18 May 2024 19:01:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

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)] [] [2020-06-11 00:35:27] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6.64	'Control'
6.54	'Control'
7.7	'Control'
6.46	'TreatA'
6.64	'TreatA'
6.84	'TreatA'
6.62	'TreatB'
6.96	'TreatB'
6.72	'TreatB'
5.8	'TreatC'
6.28	'TreatC'
6	'TreatC'
6.92	'TreatD'
6.38	'TreatD'
8.64	'TreatD'

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319172&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319172&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319172&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 time1 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
Response ~ Treatment
means6.96-0.313-0.193-0.9330.353

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response  ~  Treatment \tabularnewline
means & 6.96 & -0.313 & -0.193 & -0.933 & 0.353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319172&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]6.96[/C][C]-0.313[/C][C]-0.193[/C][C]-0.933[/C][C]0.353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319172&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319172&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
Response ~ Treatment
means6.96-0.313-0.193-0.9330.353






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment42.6860.6721.7390.218
Residuals103.8620.386 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 4 & 2.686 & 0.672 & 1.739 & 0.218 \tabularnewline
Residuals & 10 & 3.862 & 0.386 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319172&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]Treatment[/C][C]4[/C][C]2.686[/C][C]0.672[/C][C]1.739[/C][C]0.218[/C][/ROW]
[ROW][C]Residuals[/C][C]10[/C][C]3.862[/C][C]0.386[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319172&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319172&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)
Treatment42.6860.6721.7390.218
Residuals103.8620.386






Tukey Honest Significant Difference Comparisons
difflwruprp adj
TreatA-Control-0.313-1.9831.3570.969
TreatB-Control-0.193-1.8631.4770.995
TreatC-Control-0.933-2.6030.7370.405
TreatD-Control0.353-1.3172.0230.953
TreatB-TreatA0.12-1.551.790.999
TreatC-TreatA-0.62-2.291.050.74
TreatD-TreatA0.667-1.0032.3370.69
TreatC-TreatB-0.74-2.410.930.608
TreatD-TreatB0.547-1.1232.2170.814
TreatD-TreatC1.287-0.3832.9570.158

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
TreatA-Control & -0.313 & -1.983 & 1.357 & 0.969 \tabularnewline
TreatB-Control & -0.193 & -1.863 & 1.477 & 0.995 \tabularnewline
TreatC-Control & -0.933 & -2.603 & 0.737 & 0.405 \tabularnewline
TreatD-Control & 0.353 & -1.317 & 2.023 & 0.953 \tabularnewline
TreatB-TreatA & 0.12 & -1.55 & 1.79 & 0.999 \tabularnewline
TreatC-TreatA & -0.62 & -2.29 & 1.05 & 0.74 \tabularnewline
TreatD-TreatA & 0.667 & -1.003 & 2.337 & 0.69 \tabularnewline
TreatC-TreatB & -0.74 & -2.41 & 0.93 & 0.608 \tabularnewline
TreatD-TreatB & 0.547 & -1.123 & 2.217 & 0.814 \tabularnewline
TreatD-TreatC & 1.287 & -0.383 & 2.957 & 0.158 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319172&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]TreatA-Control[/C][C]-0.313[/C][C]-1.983[/C][C]1.357[/C][C]0.969[/C][/ROW]
[ROW][C]TreatB-Control[/C][C]-0.193[/C][C]-1.863[/C][C]1.477[/C][C]0.995[/C][/ROW]
[ROW][C]TreatC-Control[/C][C]-0.933[/C][C]-2.603[/C][C]0.737[/C][C]0.405[/C][/ROW]
[ROW][C]TreatD-Control[/C][C]0.353[/C][C]-1.317[/C][C]2.023[/C][C]0.953[/C][/ROW]
[ROW][C]TreatB-TreatA[/C][C]0.12[/C][C]-1.55[/C][C]1.79[/C][C]0.999[/C][/ROW]
[ROW][C]TreatC-TreatA[/C][C]-0.62[/C][C]-2.29[/C][C]1.05[/C][C]0.74[/C][/ROW]
[ROW][C]TreatD-TreatA[/C][C]0.667[/C][C]-1.003[/C][C]2.337[/C][C]0.69[/C][/ROW]
[ROW][C]TreatC-TreatB[/C][C]-0.74[/C][C]-2.41[/C][C]0.93[/C][C]0.608[/C][/ROW]
[ROW][C]TreatD-TreatB[/C][C]0.547[/C][C]-1.123[/C][C]2.217[/C][C]0.814[/C][/ROW]
[ROW][C]TreatD-TreatC[/C][C]1.287[/C][C]-0.383[/C][C]2.957[/C][C]0.158[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319172&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319172&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
TreatA-Control-0.313-1.9831.3570.969
TreatB-Control-0.193-1.8631.4770.995
TreatC-Control-0.933-2.6030.7370.405
TreatD-Control0.353-1.3172.0230.953
TreatB-TreatA0.12-1.551.790.999
TreatC-TreatA-0.62-2.291.050.74
TreatD-TreatA0.667-1.0032.3370.69
TreatC-TreatB-0.74-2.410.930.608
TreatD-TreatB0.547-1.1232.2170.814
TreatD-TreatC1.287-0.3832.9570.158






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group40.9580.471
10 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 0.958 & 0.471 \tabularnewline
  & 10 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319172&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]0.958[/C][C]0.471[/C][/ROW]
[ROW][C] [/C][C]10[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319172&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319172&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)
Group40.9580.471
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 <- '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')