Free Statistics

of Irreproducible Research!

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 computationMon, 05 Nov 2012 19:25:02 -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/2012/Nov/05/t1352161551l08g4ktcl84jrc2.htm/, Retrieved Sun, 05 Feb 2023 23:34:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=186411, Retrieved Sun, 05 Feb 2023 23:34:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
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)] [MOMAGE WISCRY7V] [2012-11-05 23:25:03] [74be16979710d4c4e7c6647856088456]
-   PD  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [MVRBIQ0 MVIQ] [2012-11-06 00:16:23] [74be16979710d4c4e7c6647856088456]
-    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [MSCORES MWARM30] [2012-11-06 00:25:02] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1	3
1	6
2	8
2	8
2	7
1	5
2	7
2	8
3	9
3	9
1	3
3	9
2	7
3	9
2	8
1	6
2	7
2	8
3	9
2	7
1	6
2	8
2	7
2	7
2	8
3	9
3	9
2	7
1	4
2	7
2	7
3	9
2	7
3	9
3	10
1	5
1	6
3	9
3	9
2	8
1	6
1	6
1	5
2	8
2	8
1	5
1	6
3	9
2	8
1	4
2	8
3	9
2	7
2	7
1	6
3	9
3	9
2	8
1	4
1	6
3	10
2	8
2	7
2	7
2	8
1	3
2	8
3	10
2	7
1	5
3	10
1	5
2	8
3	9
1	6
3	9
2	8
1	5
2	8
1	3
2	7
2	8
3	10
3	9
3	10
3	9
2	8
2	8
2	8
3	9
1	4
1	6
2	7
1	4
3	9
2	7
2	8
2	7
2	8
2	7
2	7
3	9
2	8
2	8
3	9
3	9
3	10
2	7
2	8
1	5
3	9
2	8
2	7
2	8
2	8
2	7
1	6
2	7
2	7
1	6
1	6
2	7
3	9
1	6
3	10
1	4
2	8
2	7
3	10
2	7
1	5
3	9
2	8
3	9
2	8
2	8
3	9
2	8
3	9
2	7
1	6
2	8
1	6
1	5
1	3
1	6
2	8
2	7
2	8
1	6
3	9
3	9
3	10
2	7
1	5
2	8
3	9
2	8
2	8
1	4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186411&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186411&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186411&T=0

As an alternative you can also use a 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'George Udny Yule' @ yule.wessa.net







ANOVA Model
MWARM30 ~ MSCORES
means5.0482.5124.185

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MWARM30  ~  MSCORES \tabularnewline
means & 5.048 & 2.512 & 4.185 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186411&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MWARM30  ~  MSCORES[/C][/ROW]
[ROW][C]means[/C][C]5.048[/C][C]2.512[/C][C]4.185[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186411&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186411&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
MWARM30 ~ MSCORES
means5.0482.5124.185







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MSCORES2378.341189.17412.1580
Residuals15772.0590.459

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MSCORES & 2 & 378.341 & 189.17 & 412.158 & 0 \tabularnewline
Residuals & 157 & 72.059 & 0.459 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186411&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]MSCORES[/C][C]2[/C][C]378.341[/C][C]189.17[/C][C]412.158[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]157[/C][C]72.059[/C][C]0.459[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186411&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186411&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MSCORES2378.341189.17412.1580
Residuals15772.0590.459







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-12.5122.2032.8210
3-14.1853.8374.5330
3-21.6731.3661.9790

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 2.512 & 2.203 & 2.821 & 0 \tabularnewline
3-1 & 4.185 & 3.837 & 4.533 & 0 \tabularnewline
3-2 & 1.673 & 1.366 & 1.979 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186411&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]2.512[/C][C]2.203[/C][C]2.821[/C][C]0[/C][/ROW]
[ROW][C]3-1[/C][C]4.185[/C][C]3.837[/C][C]4.533[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]1.673[/C][C]1.366[/C][C]1.979[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186411&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186411&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-12.5122.2032.8210
3-14.1853.8374.5330
3-21.6731.3661.9790







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group216.5310
157

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 16.531 & 0 \tabularnewline
  & 157 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186411&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]2[/C][C]16.531[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]157[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186411&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186411&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group216.5310
157



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; 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){
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<-levene.test(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')