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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 computationSun, 03 Nov 2013 11:03:30 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/03/t1383494619lhysda80x52765z.htm/, Retrieved Mon, 29 Apr 2024 08:33:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221951, Retrieved Mon, 29 Apr 2024 08:33:01 +0000
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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)] [Ws 5 vraag 6] [2013-11-03 16:03:30] [4c736a442787d42e94a9d9bc48424aaa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1 1
-1 1
1 1.5
0 0
0 0
0 1
0 1
1 1
1 2
-1 1
0 2
1 0
1 0
0 2
NA NA
0 1
-1 1
0 -0.5
1 2
1 0
0 1
-1 -1
NA NA
NA NA
0 1
0 -1
NA NA
NA NA
0 2
0 0
-1 -0.5
-1 1
1 0.5
NA NA
1 0.5
NA NA
-1 1
1 0
1 1
0 1
0 0
0 1
-1 -1
0 -0.5
1 0
1 2
0 0
-1 0
0 1
0 0.5
1 2
0 1
1 2
NA NA
0 0
1 0
1 0.5
NA NA
0 2
NA NA
1 0
0 1
0 0
0 -1
1 2
0 1
1 2
0 0
0 0
0 1
0 0
0 0
0 0
0 0
0 1
0 1
1 2
0 1
0 1
0 1
1 2
1 2
1 2
0 1
NA NA
1 2
NA NA
0 1
1 2
NA NA
-1 -1
0 1
NA NA
1 2
0 1
0 1
0 1
0 1
NA NA
0 0
-1 -1
1 2
0 0
1 2
0 0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221951&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221951&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221951&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
Exp1_post3-pre ~ Exp1_post4-pre
means-0.333-0.3330.5831.0830.2081.3331.133

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Exp1_post3-pre  ~  Exp1_post4-pre \tabularnewline
means & -0.333 & -0.333 & 0.583 & 1.083 & 0.208 & 1.333 & 1.133 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221951&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Exp1_post3-pre  ~  Exp1_post4-pre[/C][/ROW]
[ROW][C]means[/C][C]-0.333[/C][C]-0.333[/C][C]0.583[/C][C]1.083[/C][C]0.208[/C][C]1.333[/C][C]1.133[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221951&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221951&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
Exp1_post3-pre ~ Exp1_post4-pre
means-0.333-0.3330.5831.0830.2081.3331.133






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Exp1_post4-pre617.8392.97312.3690
Residuals8319.950.24 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Exp1_post4-pre & 6 & 17.839 & 2.973 & 12.369 & 0 \tabularnewline
Residuals & 83 & 19.95 & 0.24 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221951&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]Exp1_post4-pre[/C][C]6[/C][C]17.839[/C][C]2.973[/C][C]12.369[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]83[/C][C]19.95[/C][C]0.24[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221951&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221951&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)
Exp1_post4-pre617.8392.97312.3690
Residuals8319.950.24






Tukey Honest Significant Difference Comparisons
difflwruprp adj
-1--0.5-0.333-1.3810.7140.961
0--0.50.583-0.3241.4910.458
0.5--0.51.083-0.0482.2150.07
1--0.50.208-0.6861.1030.992
1.5--0.51.333-0.3773.0440.231
2--0.51.1330.2162.0510.006
0--10.9170.241.5930.002
0.5--11.4170.462.3730
1--10.542-0.1171.2010.179
1.5--11.6670.0663.2670.036
2--11.4670.7772.1560
0.5-00.5-0.31.30.494
1-0-0.375-0.7750.0250.081
1.5-00.75-0.7622.2620.745
2-00.550.1010.9990.007
1-0.5-0.875-1.661-0.0890.019
1.5-0.50.25-1.4061.9060.999
2-0.50.05-0.7610.8611
1.5-11.125-0.3792.6290.276
2-10.9250.5031.3470
2-1.5-0.2-1.7181.3181

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
-1--0.5 & -0.333 & -1.381 & 0.714 & 0.961 \tabularnewline
0--0.5 & 0.583 & -0.324 & 1.491 & 0.458 \tabularnewline
0.5--0.5 & 1.083 & -0.048 & 2.215 & 0.07 \tabularnewline
1--0.5 & 0.208 & -0.686 & 1.103 & 0.992 \tabularnewline
1.5--0.5 & 1.333 & -0.377 & 3.044 & 0.231 \tabularnewline
2--0.5 & 1.133 & 0.216 & 2.051 & 0.006 \tabularnewline
0--1 & 0.917 & 0.24 & 1.593 & 0.002 \tabularnewline
0.5--1 & 1.417 & 0.46 & 2.373 & 0 \tabularnewline
1--1 & 0.542 & -0.117 & 1.201 & 0.179 \tabularnewline
1.5--1 & 1.667 & 0.066 & 3.267 & 0.036 \tabularnewline
2--1 & 1.467 & 0.777 & 2.156 & 0 \tabularnewline
0.5-0 & 0.5 & -0.3 & 1.3 & 0.494 \tabularnewline
1-0 & -0.375 & -0.775 & 0.025 & 0.081 \tabularnewline
1.5-0 & 0.75 & -0.762 & 2.262 & 0.745 \tabularnewline
2-0 & 0.55 & 0.101 & 0.999 & 0.007 \tabularnewline
1-0.5 & -0.875 & -1.661 & -0.089 & 0.019 \tabularnewline
1.5-0.5 & 0.25 & -1.406 & 1.906 & 0.999 \tabularnewline
2-0.5 & 0.05 & -0.761 & 0.861 & 1 \tabularnewline
1.5-1 & 1.125 & -0.379 & 2.629 & 0.276 \tabularnewline
2-1 & 0.925 & 0.503 & 1.347 & 0 \tabularnewline
2-1.5 & -0.2 & -1.718 & 1.318 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221951&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]-1--0.5[/C][C]-0.333[/C][C]-1.381[/C][C]0.714[/C][C]0.961[/C][/ROW]
[ROW][C]0--0.5[/C][C]0.583[/C][C]-0.324[/C][C]1.491[/C][C]0.458[/C][/ROW]
[ROW][C]0.5--0.5[/C][C]1.083[/C][C]-0.048[/C][C]2.215[/C][C]0.07[/C][/ROW]
[ROW][C]1--0.5[/C][C]0.208[/C][C]-0.686[/C][C]1.103[/C][C]0.992[/C][/ROW]
[ROW][C]1.5--0.5[/C][C]1.333[/C][C]-0.377[/C][C]3.044[/C][C]0.231[/C][/ROW]
[ROW][C]2--0.5[/C][C]1.133[/C][C]0.216[/C][C]2.051[/C][C]0.006[/C][/ROW]
[ROW][C]0--1[/C][C]0.917[/C][C]0.24[/C][C]1.593[/C][C]0.002[/C][/ROW]
[ROW][C]0.5--1[/C][C]1.417[/C][C]0.46[/C][C]2.373[/C][C]0[/C][/ROW]
[ROW][C]1--1[/C][C]0.542[/C][C]-0.117[/C][C]1.201[/C][C]0.179[/C][/ROW]
[ROW][C]1.5--1[/C][C]1.667[/C][C]0.066[/C][C]3.267[/C][C]0.036[/C][/ROW]
[ROW][C]2--1[/C][C]1.467[/C][C]0.777[/C][C]2.156[/C][C]0[/C][/ROW]
[ROW][C]0.5-0[/C][C]0.5[/C][C]-0.3[/C][C]1.3[/C][C]0.494[/C][/ROW]
[ROW][C]1-0[/C][C]-0.375[/C][C]-0.775[/C][C]0.025[/C][C]0.081[/C][/ROW]
[ROW][C]1.5-0[/C][C]0.75[/C][C]-0.762[/C][C]2.262[/C][C]0.745[/C][/ROW]
[ROW][C]2-0[/C][C]0.55[/C][C]0.101[/C][C]0.999[/C][C]0.007[/C][/ROW]
[ROW][C]1-0.5[/C][C]-0.875[/C][C]-1.661[/C][C]-0.089[/C][C]0.019[/C][/ROW]
[ROW][C]1.5-0.5[/C][C]0.25[/C][C]-1.406[/C][C]1.906[/C][C]0.999[/C][/ROW]
[ROW][C]2-0.5[/C][C]0.05[/C][C]-0.761[/C][C]0.861[/C][C]1[/C][/ROW]
[ROW][C]1.5-1[/C][C]1.125[/C][C]-0.379[/C][C]2.629[/C][C]0.276[/C][/ROW]
[ROW][C]2-1[/C][C]0.925[/C][C]0.503[/C][C]1.347[/C][C]0[/C][/ROW]
[ROW][C]2-1.5[/C][C]-0.2[/C][C]-1.718[/C][C]1.318[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221951&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221951&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
-1--0.5-0.333-1.3810.7140.961
0--0.50.583-0.3241.4910.458
0.5--0.51.083-0.0482.2150.07
1--0.50.208-0.6861.1030.992
1.5--0.51.333-0.3773.0440.231
2--0.51.1330.2162.0510.006
0--10.9170.241.5930.002
0.5--11.4170.462.3730
1--10.542-0.1171.2010.179
1.5--11.6670.0663.2670.036
2--11.4670.7772.1560
0.5-00.5-0.31.30.494
1-0-0.375-0.7750.0250.081
1.5-00.75-0.7622.2620.745
2-00.550.1010.9990.007
1-0.5-0.875-1.661-0.0890.019
1.5-0.50.25-1.4061.9060.999
2-0.50.05-0.7610.8611
1.5-11.125-0.3792.6290.276
2-10.9250.5031.3470
2-1.5-0.2-1.7181.3181






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group60.2530.957
83 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 6 & 0.253 & 0.957 \tabularnewline
  & 83 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221951&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]6[/C][C]0.253[/C][C]0.957[/C][/ROW]
[ROW][C] [/C][C]83[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221951&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221951&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)
Group60.2530.957
83


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')