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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, 21 Dec 2017 15:07:25 +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/2017/Dec/21/t1513866174hx7j62d4t3csk9m.htm/, Retrieved Tue, 14 May 2024 13:59:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310649, Retrieved Tue, 14 May 2024 13:59:57 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact43

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)] [] [2017-12-21 14:07:25] [767bae2faba658f23149559b7968621e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10 5
8 5
8 3
9 3
5 5
10 4
8 4
9 5
8 1
7 4
10 4
10 1
9 3
4 2
4 3
8 4
9 3
10 2
8 3
5 3
10 4
8 4
7 4
8 4
8 3
9 4
8 4
6 3
8 3
8 3
5 4
9 4
8 4
8 4
8 3
6 1
6 3
9 4
8 4
9 4
10 4
8 4
8 4
7 3
7 3
10 2
8 4
7 3
10 3
7 4
7 3
9 3
9 5
8 3
6 4
8 4
9 4
2 4
6 4
8 4
8 4
7 4
8 2
6 4
10 4
10 4
10 2
8 3
8 5
7 4
10 5
5 3
3 2
2 2
3 2
4 4
2 2
6 4
8 4
8 4
5 4
10 5
9 4
8 4
9 4
8 3
5 3
7 3
9 5
8 4
4 3
7 3
8 3
7 3
7 3
9 3
6 3
7 3
4 3
6 3
10 4
9 4
10 5
8 4
4 3
8 3
5 5
8 3
9 3
8 3
4 5
8 4
10 5
6 2
7 3
10 4
9 4
8 5
3 4
8 4
7 4
7 4
8 4
8 4
7 5
7 3
9 4
9 4
9 2
4 4
6 4
6 2
6 3
8 3
3 4
8 3
8 4
6 2
10 4
2 4
9 3
6 3
6 4
5 2
4 4
7 2
5 3
8 4
6 3
9 4
6 3
4 2
7 4
2 1
8 3
9 4
6 3
5 4
7 3
8 4
4 3
9 3
9 3
9 5
7 3
5 3
7 4
9 4
8 2
6 3
9 5
8 3
7 3
7 3
7 3
8 3
10 5
6 4
6 4

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=310649&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=310649&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310649&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
Intention_to_Use ~ It_is_easy_to_find_the_information_I_need
means6.5-0.4410.5631.0261.833

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Intention_to_Use  ~  It_is_easy_to_find_the_information_I_need \tabularnewline
means & 6.5 & -0.441 & 0.563 & 1.026 & 1.833 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310649&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Intention_to_Use  ~  It_is_easy_to_find_the_information_I_need[/C][/ROW]
[ROW][C]means[/C][C]6.5[/C][C]-0.441[/C][C]0.563[/C][C]1.026[/C][C]1.833[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310649&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310649&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
Intention_to_Use ~ It_is_easy_to_find_the_information_I_need
means6.5-0.4410.5631.0261.833






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
It_is_easy_to_find_the_information_I_need455.39513.8493.8210.005
Residuals174630.6393.624 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
It_is_easy_to_find_the_information_I_need & 4 & 55.395 & 13.849 & 3.821 & 0.005 \tabularnewline
Residuals & 174 & 630.639 & 3.624 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310649&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]It_is_easy_to_find_the_information_I_need[/C][C]4[/C][C]55.395[/C][C]13.849[/C][C]3.821[/C][C]0.005[/C][/ROW]
[ROW][C]Residuals[/C][C]174[/C][C]630.639[/C][C]3.624[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310649&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310649&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)
It_is_easy_to_find_the_information_I_need455.39513.8493.8210.005
Residuals174630.6393.624






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-1-0.441-3.3582.4750.994
3-10.563-2.1423.2670.979
4-11.026-1.6663.7180.831
5-11.833-1.0684.7340.411
3-21.004-0.4282.4360.304
4-21.4670.062.8750.036
5-22.2750.54.0490.005
4-30.464-0.4271.3540.605
5-31.271-0.1292.6710.095
5-40.807-0.5692.1830.488

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & -0.441 & -3.358 & 2.475 & 0.994 \tabularnewline
3-1 & 0.563 & -2.142 & 3.267 & 0.979 \tabularnewline
4-1 & 1.026 & -1.666 & 3.718 & 0.831 \tabularnewline
5-1 & 1.833 & -1.068 & 4.734 & 0.411 \tabularnewline
3-2 & 1.004 & -0.428 & 2.436 & 0.304 \tabularnewline
4-2 & 1.467 & 0.06 & 2.875 & 0.036 \tabularnewline
5-2 & 2.275 & 0.5 & 4.049 & 0.005 \tabularnewline
4-3 & 0.464 & -0.427 & 1.354 & 0.605 \tabularnewline
5-3 & 1.271 & -0.129 & 2.671 & 0.095 \tabularnewline
5-4 & 0.807 & -0.569 & 2.183 & 0.488 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310649&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]-0.441[/C][C]-3.358[/C][C]2.475[/C][C]0.994[/C][/ROW]
[ROW][C]3-1[/C][C]0.563[/C][C]-2.142[/C][C]3.267[/C][C]0.979[/C][/ROW]
[ROW][C]4-1[/C][C]1.026[/C][C]-1.666[/C][C]3.718[/C][C]0.831[/C][/ROW]
[ROW][C]5-1[/C][C]1.833[/C][C]-1.068[/C][C]4.734[/C][C]0.411[/C][/ROW]
[ROW][C]3-2[/C][C]1.004[/C][C]-0.428[/C][C]2.436[/C][C]0.304[/C][/ROW]
[ROW][C]4-2[/C][C]1.467[/C][C]0.06[/C][C]2.875[/C][C]0.036[/C][/ROW]
[ROW][C]5-2[/C][C]2.275[/C][C]0.5[/C][C]4.049[/C][C]0.005[/C][/ROW]
[ROW][C]4-3[/C][C]0.464[/C][C]-0.427[/C][C]1.354[/C][C]0.605[/C][/ROW]
[ROW][C]5-3[/C][C]1.271[/C][C]-0.129[/C][C]2.671[/C][C]0.095[/C][/ROW]
[ROW][C]5-4[/C][C]0.807[/C][C]-0.569[/C][C]2.183[/C][C]0.488[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310649&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310649&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
2-1-0.441-3.3582.4750.994
3-10.563-2.1423.2670.979
4-11.026-1.6663.7180.831
5-11.833-1.0684.7340.411
3-21.004-0.4282.4360.304
4-21.4670.062.8750.036
5-22.2750.54.0490.005
4-30.464-0.4271.3540.605
5-31.271-0.1292.6710.095
5-40.807-0.5692.1830.488






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group43.3770.011
174 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 3.377 & 0.011 \tabularnewline
  & 174 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310649&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]3.377[/C][C]0.011[/C][/ROW]
[ROW][C] [/C][C]174[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310649&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310649&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)
Group43.3770.011
174


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par3 = TRUE ;
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')