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Author's title

Author*Unverified author*
R Software ModuleIan.Hollidayrwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationTue, 30 Nov 2010 14:32:59 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/30/t1291127598f59d63teg3i7w7p.htm/, Retrieved Thu, 31 Oct 2024 22:50:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103538, Retrieved Thu, 31 Oct 2024 22:50:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
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]
-   PD        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-29 14:04:48] [74be16979710d4c4e7c6647856088456]
-   P           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-29 14:32:01] [74be16979710d4c4e7c6647856088456]
-   PD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-29 15:15:52] [74be16979710d4c4e7c6647856088456]
-                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-30 14:32:59] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
2	1	1	44	88
1	1	1	39	79
2	1	1	34	90
2	2	1	56	98
2	1	1	39	80
3	1	1	51	96
1	1	1	50	87
1	2	1	44	101
3	2	1	48	85
1	2	1	52	94
1	1	1	44	68
2	1	1	52	91
2	1	1	55	70
3	1	1	36	68
3	1	1	39	70
3	1	1	39	112
3	1	1	56	96
1	2	1	42	80
2	2	1	30	94
3	2	1	39	86
2	2	1	48	87
3	1	1	46	81
3	1	1	59	96
2	1	1	52	90
2	1	1	46	77
2	1	1	49	95
3	1	1	62	101
1	2	1	41	70
3	2	1	50	88
3	2	1	48	98
2	2	1	54	92
1	2	1	36	88
1	2	1	36	94
2	2	1	44	75
3	2	1	54	97
2	2	1	30	78
2	2	1	39	91
2	3	1	52	88
3	3	1	39	91
3	3	1	43	88
3	1	2	57	102
1	1	2	44	85
3	1	2	32	73
3	1	2	55	92
3	1	2	41	77
2	1	2	55	95
2	1	2	44	75
2	1	2	55	86
3	1	2	44	79
3	2	2	46	97
1	2	2	54	107
1	2	2	43	77
2	2	2	39	80
3	2	2	43	86
2	2	2	57	100
3	2	2	55	86
3	2	2	44	86
3	2	2	37	90
2	2	2	54	97
2	2	2	39	79
3	2	2	52	92
3	2	2	44	95
3	2	2	41	90
2	2	2	62	95
2	2	2	37	87
3	3	2	43	109
3	3	2	41	88
2	3	2	48	108
3	3	2	58	111
3	1	2	41	87
1	1	2	56	102
2	1	2	48	90
1	1	2	31	75
2	1	2	43	90
2	1	2	57	97
1	1	2	46	95
3	1	2	43	86
3	1	2	45	77
3	1	2	46	95
1	1	2	59	90
3	1	2	50	95
2	2	2	48	97
3	2	2	59	97
3	2	2	44	101
1	2	2	50	94
3	2	2	41	90
3	2	2	46	95
3	2	2	52	97
3	2	2	59	100
3	2	2	41	68
3	2	2	37	87
1	2	2	59	103
3	2	2	59	115
3	2	2	56	94
1	2	2	66	98
3	2	2	55	94
3	2	2	32	68
3	2	2	50	96
3	2	2	46	106
2	2	2	56	100
2	2	2	55	91
3	2	2	57	94
3	2	2	34	86
2	2	2	58	95
1	3	2	37	95
2	3	2	46	102
3	3	2	39	103
3	3	2	48	90
3	3	2	66	107
1	1	3	30	84
3	1	3	54	97
3	1	3	60	97
3	1	3	60	86
3	1	3	37	72
2	1	3	48	78
1	1	3	48	78
1	1	3	54	85
1	1	3	30	75
3	1	3	41	86
3	1	3	50	97
1	2	3	52	97
2	2	3	48	75
2	2	3	55	97
1	2	3	52	82
3	2	3	60	98
3	2	3	52	98
3	2	3	34	92
3	2	3	36	85
1	2	3	50	84
3	2	3	46	94
3	2	3	52	90
2	3	3	54	107
3	3	3	60	92
1	3	3	56	87
2	3	3	55	111
1	3	3	62	96
1	3	3	50	101
3	3	3	56	88
1	3	3	66	109
2	3	3	52	111
1	3	3	50	115
2	3	3	50	91
3	1	3	58	101
3	2	3	57	95
1	2	3	50	87
3	2	3	52	92
3	2	3	46	101
2	2	3	50	106
1	3	3	54	101
3	3	3	66	115
1	3	3	59	115




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103538&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103538&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103538&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'RServer@AstonUniversity' @ vre.aston.ac.uk







ANOVA Model
MC30VRB ~ MWARM30
means45.4252.7635.813

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MWARM30 \tabularnewline
means & 45.425 & 2.763 & 5.813 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103538&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]45.425[/C][C]2.763[/C][C]5.813[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103538&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103538&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
MC30VRB ~ MWARM30
means45.4252.7635.813







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM302694.042347.0215.0380.008
Residuals14810193.94568.878

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 2 & 694.042 & 347.021 & 5.038 & 0.008 \tabularnewline
Residuals & 148 & 10193.945 & 68.878 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103538&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]MWARM30[/C][C]2[/C][C]694.042[/C][C]347.021[/C][C]5.038[/C][C]0.008[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]10193.945[/C][C]68.878[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103538&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103538&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)
MWARM302694.042347.0215.0380.008
Residuals14810193.94568.878







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-12.763-1.1416.6680.218
3-15.8131.47210.1540.005
3-23.05-0.7966.8950.149

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 2.763 & -1.141 & 6.668 & 0.218 \tabularnewline
3-1 & 5.813 & 1.472 & 10.154 & 0.005 \tabularnewline
3-2 & 3.05 & -0.796 & 6.895 & 0.149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103538&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]2.763[/C][C]-1.141[/C][C]6.668[/C][C]0.218[/C][/ROW]
[ROW][C]3-1[/C][C]5.813[/C][C]1.472[/C][C]10.154[/C][C]0.005[/C][/ROW]
[ROW][C]3-2[/C][C]3.05[/C][C]-0.796[/C][C]6.895[/C][C]0.149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103538&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103538&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
2-12.763-1.1416.6680.218
3-15.8131.47210.1540.005
3-23.05-0.7966.8950.149







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.6380.53
148

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.638 & 0.53 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103538&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]0.638[/C][C]0.53[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103538&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103538&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)
Group20.6380.53
148



Parameters (Session):
par1 = 4 ; par2 = 3 ; par3 = TRUE ;
Parameters (R input):
par1 = 4 ; par2 = 3 ; par3 = TRUE ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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()
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')