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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 computationMon, 28 Nov 2011 12:04:41 -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/2011/Nov/28/t1322499895a6u5ymxw4fqkdya.htm/, Retrieved Thu, 31 Oct 2024 23:27:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147880, Retrieved Thu, 31 Oct 2024 23:27:30 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Comparison of a m...] [2011-11-28 15:08:47] [221b3b4216f0c3837d81a9a9f89ff273]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-28 17:04:41] [10859d22281cca92ea91c7e9bff5476e] [Current]
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Dataseries X:
88	1
94	2
90	2
73	1
68	1
80	1
86	2
86	2
91	1
79	3
96	1
92	3
72	2
96	1
70	2
86	2
87	2
88	1
79	3
90	2
95	1
85	1
90	1
115	1
84	2
79	3
94	2
97	2
86	2
111	2
87	2
98	3
87	2
68	2
88	2
82	1
111	2
75	3
94	3
95	1
80	2
95	1
68	2
94	3
88	2
84	2
101	3
98	1
78	1
109	2
102	2
81	1
97	3
75	1
97	1
101	1
101	2
95	2
95	2
95	2
90	1
107	2
92	2
86	2
70	2
95	2
96	3
91	2
87	1
92	1
97	2
102	2
91	2
68	3
88	2
97	2
90	3
101	1
94	2
101	1
109	2
100	2
103	3
94	2
97	3
85	3
75	2
77	2
87	2
78	2
108	2
97	2
105	1
106	1
107	1
95	3
107	2
115	2
101	2
85	2
90	1
115	3
95	2
97	2
112	1
97	2
77	3
90	2
94	1
103	1
77	1
98	1
90	2
111	2
77	3
88	2
75	2
92	2
78	3
106	2
80	3
87	1
92	2
111	2
86	2
85	1
90	2
101	1
94	3
86	3
86	2
90	2
75	1
86	3
91	2
97	1
91	1
70	1
98	1
96	2
95	3
100	2
95	2
97	1
97	2
92	1
115	1
88	2
87	2
100	2
98	2
102	3
96	3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=147880&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=147880&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147880&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.







ANOVA Model
WISCRY7V ~ MVRBIQ0
means92.130.047-2.559

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MVRBIQ0
 \tabularnewline
means & 92.13 & 0.047 & -2.559 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147880&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MVRBIQ0
[/C][/ROW]
[ROW][C]means[/C][C]92.13[/C][C]0.047[/C][C]-2.559[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147880&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147880&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
WISCRY7V ~ MVRBIQ0
means92.130.047-2.559







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ0 2153.34876.6740.6590.519
Residuals15017443.594116.291

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0
 & 2 & 153.348 & 76.674 & 0.659 & 0.519 \tabularnewline
Residuals & 150 & 17443.594 & 116.291 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147880&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]MVRBIQ0
[/C][C]2[/C][C]153.348[/C][C]76.674[/C][C]0.659[/C][C]0.519[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]17443.594[/C][C]116.291[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147880&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147880&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)
MVRBIQ0 2153.34876.6740.6590.519
Residuals15017443.594116.291







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10.047-4.6884.7811
3-1-2.559-8.6783.560.584
3-2-2.606-8.223.0090.516

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 0.047 & -4.688 & 4.781 & 1 \tabularnewline
3-1 & -2.559 & -8.678 & 3.56 & 0.584 \tabularnewline
3-2 & -2.606 & -8.22 & 3.009 & 0.516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147880&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]0.047[/C][C]-4.688[/C][C]4.781[/C][C]1[/C][/ROW]
[ROW][C]3-1[/C][C]-2.559[/C][C]-8.678[/C][C]3.56[/C][C]0.584[/C][/ROW]
[ROW][C]3-2[/C][C]-2.606[/C][C]-8.22[/C][C]3.009[/C][C]0.516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147880&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147880&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
2-10.047-4.6884.7811
3-1-2.559-8.6783.560.584
3-2-2.606-8.223.0090.516







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.2430.784
150

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.243 & 0.784 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147880&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]0.243[/C][C]0.784[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147880&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147880&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)
Group20.2430.784
150



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){
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')