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 computationTue, 18 Dec 2012 14:20:15 -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/Dec/18/t13558584498ikx67endkjxudt.htm/, Retrieved Fri, 29 Mar 2024 10:21:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=201586, Retrieved Fri, 29 Mar 2024 10:21:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared and McNemar Tests] [] [2010-11-16 14:33:59] [b98453cac15ba1066b407e146608df68]
- R PD  [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2012-12-10 15:11:14] [717eeab792c979f6e7c3b92a165ad49e]
- R  D    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [t 20] [2012-12-15 13:51:15] [bb9c1d1bc63af35ef3129489f33fa7df]
- RMPD      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1 way anova] [2012-12-15 14:10:59] [bb9c1d1bc63af35ef3129489f33fa7df]
- R  D        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2012-12-15 14:20:40] [bb9c1d1bc63af35ef3129489f33fa7df]
-   P             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [anova 1] [2012-12-18 19:20:15] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- R                 [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2012-12-19 15:22:19] [5b4f808c567607ef83d7f50fc3056dec]
- R                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [one-way-anova] [2012-12-21 10:06:14] [9f6ab6bc6461b94fa20254844eaa346d]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [one way anova] [2012-12-21 10:20:00] [9f6ab6bc6461b94fa20254844eaa346d]
- RMPD                [Multiple Regression] [mult. regr] [2012-12-21 10:26:08] [9f6ab6bc6461b94fa20254844eaa346d]
- RMPD                [Multiple Regression] [multipl regr] [2012-12-21 10:34:55] [9f6ab6bc6461b94fa20254844eaa346d]
-                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Anova Paper deel 5] [2012-12-21 23:19:14] [0be811ead56a6216036e70fa99791344]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Anova Paper deel ...] [2012-12-21 23:25:48] [0be811ead56a6216036e70fa99791344]
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Dataseries X:
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1	0
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0	0
1	0
0	0
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1	0
0	0
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0	0
0	0
0	0
0	0
0	0
0	0
0	0
0	0
0	0
1	0
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0	0
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0	0
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0	1
0	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201586&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]4 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=201586&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201586&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 time4 seconds
R Server'George Udny Yule' @ yule.wessa.net







ANOVA Model
T20 ~ Correct
means0.262-0.262

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
T20  ~  Correct \tabularnewline
means & 0.262 & -0.262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201586&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]T20  ~  Correct[/C][/ROW]
[ROW][C]means[/C][C]0.262[/C][C]-0.262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201586&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201586&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
T20 ~ Correct
means0.262-0.262







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Correct10.1960.1961.0310.314
Residuals6612.5540.19

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Correct & 1 & 0.196 & 0.196 & 1.031 & 0.314 \tabularnewline
Residuals & 66 & 12.554 & 0.19 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201586&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]Correct[/C][C]1[/C][C]0.196[/C][C]0.196[/C][C]1.031[/C][C]0.314[/C][/ROW]
[ROW][C]Residuals[/C][C]66[/C][C]12.554[/C][C]0.19[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201586&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201586&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)
Correct10.1960.1961.0310.314
Residuals6612.5540.19







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-0.262-0.7760.2530.314

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -0.262 & -0.776 & 0.253 & 0.314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201586&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[/C][C]-0.262[/C][C]-0.776[/C][C]0.253[/C][C]0.314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201586&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201586&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
1-0-0.262-0.7760.2530.314







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group11.0310.314
66

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 1.031 & 0.314 \tabularnewline
  & 66 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201586&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]1[/C][C]1.031[/C][C]0.314[/C][/ROW]
[ROW][C] [/C][C]66[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201586&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201586&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)
Group11.0310.314
66



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')