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of Irreproducible Research!

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 computationThu, 25 Nov 2010 12:01:48 +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/25/t1290686452igz342aw5d2etrr.htm/, Retrieved Thu, 06 Oct 2022 00:05:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=100835, Retrieved Thu, 06 Oct 2022 00:05:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
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)] [compendium 8.5] [2010-11-25 12:01:48] [15eab2c43e9c2ac9cd9b0628e098f0c4] [Current]
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Dataseries X:
1	1	6	36	88
3	1	8	56	94
3	1	8	48	90
3	1	7	32	73
1	1	5	44	68
2	1	7	39	80
3	1	8	34	86
3	1	9	41	86
2	1	9	50	91
1	1	3	39	79
1	1	9	62	96
3	1	7	52	92
3	1	9	37	72
3	1	8	50	96
1	1	6	41	70
3	1	7	55	86
3	1	8	41	87
3	1	9	56	88
2	1	7	39	79
2	1	6	52	90
1	1	8	46	95
1	1	7	44	85
3	1	8	41	90
1	1	9	50	115
1	1	9	50	84
3	1	7	44	79
1	1	4	52	94
2	1	7	54	97
3	1	7	44	86
2	1	9	52	111
2	1	7	37	87
3	1	9	52	98
1	1	10	50	87
3	1	5	36	68
3	1	6	50	88
1	1	9	52	82
2	1	9	55	111
1	1	8	31	75
1	1	6	36	94
2	1	6	49	95
1	1	5	42	80
1	1	8	37	95
3	1	8	41	68
2	1	5	30	94
2	1	6	52	88
1	1	9	30	84
1	1	4	44	101
1	1	8	66	98
2	1	9	48	78
3	1	7	43	109
3	1	7	57	102
3	1	6	46	81
3	2	9	54	97
2	2	9	48	75
2	2	8	48	97
3	2	6	62	101
3	2	10	58	101
2	2	8	58	95
2	2	7	62	95
3	2	8	46	95
2	2	3	34	90
3	2	8	66	107
3	2	10	52	92
2	2	7	55	86
2	2	5	55	70
3	2	10	57	95
3	2	5	56	96
2	2	8	55	91
1	2	9	56	87
2	2	6	54	92
2	2	9	55	97
2	2	8	46	102
2	2	5	52	91
3	2	8	32	68
2	2	3	44	88
3	2	7	46	97
1	2	8	59	90
3	2	10	46	101
3	2	9	46	94
1	2	10	54	101
1	2	9	66	109
2	2	8	56	100
1	2	8	59	103
3	2	8	57	94
1	2	9	52	97
3	2	4	48	85
2	2	6	44	75
3	2	7	41	77
1	2	4	50	87
1	2	9	48	78
2	2	7	48	108
3	2	8	59	97
3	2	8	46	106
1	2	7	54	107
2	2	7	55	95
2	2	9	54	107
3	2	8	59	115
3	2	8	44	101
1	2	9	54	85
3	2	9	52	90
3	2	10	66	115
3	2	7	44	95
2	2	8	57	97
3	2	5	39	112
3	2	9	60	97
3	2	8	45	77
3	2	7	41	90
1	2	8	50	94
3	2	8	39	103
1	2	7	43	77
3	2	6	48	98
3	2	7	37	90
3	2	7	58	111
2	2	6	46	77
3	2	6	43	88
2	2	7	44	75
3	2	9	34	92
2	2	6	30	78
2	2	10	50	106
2	2	4	39	80
3	2	8	37	87
3	2	7	55	92
3	2	5	39	86
3	2	9	36	85
2	2	8	43	90
1	2	9	50	101
3	2	8	55	94
3	2	8	43	86
3	3	9	60	86
2	3	8	48	90
1	3	9	30	75
3	3	7	43	86
3	3	6	39	91
3	3	8	52	97
2	3	6	39	91
3	3	5	39	70
2	3	3	56	98
3	3	6	59	96
3	3	8	46	95
2	3	7	57	100
3	3	8	50	95
3	3	6	54	97
3	3	9	50	97
3	3	9	60	92
1	3	10	59	115
3	3	7	41	88
2	3	5	48	87
3	3	8	59	100
3	3	9	60	98
1	3	8	56	102
3	3	4	51	96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100835&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]2 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=100835&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100835&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







ANOVA Model
WISCRY7V ~ MVRBIQ0
means88.2694.8894.861

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MVRBIQ0 \tabularnewline
means & 88.269 & 4.889 & 4.861 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100835&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]88.269[/C][C]4.889[/C][C]4.861[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100835&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100835&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
means88.2694.8894.861







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ02812.671406.3363.7060.027
Residuals14816226.945109.642

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 2 & 812.671 & 406.336 & 3.706 & 0.027 \tabularnewline
Residuals & 148 & 16226.945 & 109.642 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100835&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]812.671[/C][C]406.336[/C][C]3.706[/C][C]0.027[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]16226.945[/C][C]109.642[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100835&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100835&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)
MVRBIQ02812.671406.3363.7060.027
Residuals14816226.945109.642







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-14.8890.4279.350.028
3-14.861-1.34711.0690.156
3-2-0.027-5.9275.8721

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 4.889 & 0.427 & 9.35 & 0.028 \tabularnewline
3-1 & 4.861 & -1.347 & 11.069 & 0.156 \tabularnewline
3-2 & -0.027 & -5.927 & 5.872 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100835&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]4.889[/C][C]0.427[/C][C]9.35[/C][C]0.028[/C][/ROW]
[ROW][C]3-1[/C][C]4.861[/C][C]-1.347[/C][C]11.069[/C][C]0.156[/C][/ROW]
[ROW][C]3-2[/C][C]-0.027[/C][C]-5.927[/C][C]5.872[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100835&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100835&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
2-14.8890.4279.350.028
3-14.861-1.34711.0690.156
3-2-0.027-5.9275.8721







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.8190.443
148

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.819 & 0.443 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100835&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]0.819[/C][C]0.443[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100835&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100835&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)
Group20.8190.443
148



Parameters (Session):
par1 = 5 ; par2 = 2 ; par3 = TRUE ;
Parameters (R input):
par1 = 5 ; 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()
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')