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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 computationTue, 13 Dec 2016 14:13:58 +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/13/t1481634986r5f0m2fpc563jw3.htm/, Retrieved Sun, 05 May 2024 00:42:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299104, Retrieved Sun, 05 May 2024 00:42:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact62

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 voorb...] [2016-12-13 13:13:58] [fc6d28d208bad0c833791fcb11cb4db1] [Current]
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Dataset

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

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=299104&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=299104&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299104&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
Q1 ~ Q2
means112.6363.1773.6853

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Q1  ~  Q2 \tabularnewline
means & 1 & 1 & 2.636 & 3.177 & 3.685 & 3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299104&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Q1  ~  Q2[/C][/ROW]
[ROW][C]means[/C][C]1[/C][C]1[/C][C]2.636[/C][C]3.177[/C][C]3.685[/C][C]3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299104&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299104&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
Q1 ~ Q2
means112.6363.1773.6853






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Q2532.9596.59212.8910
Residuals16081.8180.511 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Q2 & 5 & 32.959 & 6.592 & 12.891 & 0 \tabularnewline
Residuals & 160 & 81.818 & 0.511 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299104&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]Q2[/C][C]5[/C][C]32.959[/C][C]6.592[/C][C]12.891[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]160[/C][C]81.818[/C][C]0.511[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299104&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299104&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)
Q2532.9596.59212.8910
Residuals16081.8180.511






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-11-1.9173.9170.921
3-12.6360.4824.7910.007
4-13.1771.1015.2530
5-13.6851.6085.7620
NA-130.0835.9170.04
3-21.636-0.5183.7910.248
4-22.1770.1014.2530.034
5-22.6850.6084.7620.004
NA-22-0.9174.9170.36
4-30.541-0.1231.2050.181
5-31.0490.3811.7160
NA-30.364-1.7912.5180.997
5-40.5080.1730.8430
NA-4-0.177-2.2531.8991
NA-5-0.685-2.7621.3920.932

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 1 & -1.917 & 3.917 & 0.921 \tabularnewline
3-1 & 2.636 & 0.482 & 4.791 & 0.007 \tabularnewline
4-1 & 3.177 & 1.101 & 5.253 & 0 \tabularnewline
5-1 & 3.685 & 1.608 & 5.762 & 0 \tabularnewline
NA-1 & 3 & 0.083 & 5.917 & 0.04 \tabularnewline
3-2 & 1.636 & -0.518 & 3.791 & 0.248 \tabularnewline
4-2 & 2.177 & 0.101 & 4.253 & 0.034 \tabularnewline
5-2 & 2.685 & 0.608 & 4.762 & 0.004 \tabularnewline
NA-2 & 2 & -0.917 & 4.917 & 0.36 \tabularnewline
4-3 & 0.541 & -0.123 & 1.205 & 0.181 \tabularnewline
5-3 & 1.049 & 0.381 & 1.716 & 0 \tabularnewline
NA-3 & 0.364 & -1.791 & 2.518 & 0.997 \tabularnewline
5-4 & 0.508 & 0.173 & 0.843 & 0 \tabularnewline
NA-4 & -0.177 & -2.253 & 1.899 & 1 \tabularnewline
NA-5 & -0.685 & -2.762 & 1.392 & 0.932 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299104&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]1[/C][C]-1.917[/C][C]3.917[/C][C]0.921[/C][/ROW]
[ROW][C]3-1[/C][C]2.636[/C][C]0.482[/C][C]4.791[/C][C]0.007[/C][/ROW]
[ROW][C]4-1[/C][C]3.177[/C][C]1.101[/C][C]5.253[/C][C]0[/C][/ROW]
[ROW][C]5-1[/C][C]3.685[/C][C]1.608[/C][C]5.762[/C][C]0[/C][/ROW]
[ROW][C]NA-1[/C][C]3[/C][C]0.083[/C][C]5.917[/C][C]0.04[/C][/ROW]
[ROW][C]3-2[/C][C]1.636[/C][C]-0.518[/C][C]3.791[/C][C]0.248[/C][/ROW]
[ROW][C]4-2[/C][C]2.177[/C][C]0.101[/C][C]4.253[/C][C]0.034[/C][/ROW]
[ROW][C]5-2[/C][C]2.685[/C][C]0.608[/C][C]4.762[/C][C]0.004[/C][/ROW]
[ROW][C]NA-2[/C][C]2[/C][C]-0.917[/C][C]4.917[/C][C]0.36[/C][/ROW]
[ROW][C]4-3[/C][C]0.541[/C][C]-0.123[/C][C]1.205[/C][C]0.181[/C][/ROW]
[ROW][C]5-3[/C][C]1.049[/C][C]0.381[/C][C]1.716[/C][C]0[/C][/ROW]
[ROW][C]NA-3[/C][C]0.364[/C][C]-1.791[/C][C]2.518[/C][C]0.997[/C][/ROW]
[ROW][C]5-4[/C][C]0.508[/C][C]0.173[/C][C]0.843[/C][C]0[/C][/ROW]
[ROW][C]NA-4[/C][C]-0.177[/C][C]-2.253[/C][C]1.899[/C][C]1[/C][/ROW]
[ROW][C]NA-5[/C][C]-0.685[/C][C]-2.762[/C][C]1.392[/C][C]0.932[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299104&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299104&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
2-11-1.9173.9170.921
3-12.6360.4824.7910.007
4-13.1771.1015.2530
5-13.6851.6085.7620
NA-130.0835.9170.04
3-21.636-0.5183.7910.248
4-22.1770.1014.2530.034
5-22.6850.6084.7620.004
NA-22-0.9174.9170.36
4-30.541-0.1231.2050.181
5-31.0490.3811.7160
NA-30.364-1.7912.5180.997
5-40.5080.1730.8430
NA-4-0.177-2.2531.8991
NA-5-0.685-2.7621.3920.932






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group51.8280.11
160 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.828 & 0.11 \tabularnewline
  & 160 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299104&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]1.828[/C][C]0.11[/C][/ROW]
[ROW][C] [/C][C]160[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299104&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299104&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)
Group51.8280.11
160


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):
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')