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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 computationFri, 25 Nov 2011 08:40:38 -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/25/t1322228459l6bzgdy1jdjziuu.htm/, Retrieved Thu, 28 Mar 2024 18:17:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147312, Retrieved Thu, 28 Mar 2024 18:17:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
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 PD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers Age Gests...] [2011-11-24 13:11:47] [84f9d24ffbb976b91a97c3ec996667ce]
-   P             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers Age Gests...] [2011-11-24 13:16:14] [84f9d24ffbb976b91a97c3ec996667ce]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-25 12:47:21] [74be16979710d4c4e7c6647856088456]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-25 13:40:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1	39	79
1	34	90
1	44	88
1	56	98
1	52	94
1	44	101
1	48	85
1	50	87
1	39	80
1	51	96
1	44	68
1	36	68
1	42	80
1	30	94
1	55	70
1	56	96
1	52	91
1	39	112
1	39	86
1	39	70
1	48	87
1	36	88
1	41	70
1	52	90
1	50	88
1	36	94
1	49	95
1	52	88
1	46	81
1	62	101
1	54	92
1	44	75
1	48	98
1	46	77
1	43	88
1	30	78
1	39	91
1	39	91
1	59	96
1	54	97
1	32	73
2	39	80
2	52	92
2	55	86
2	39	79
2	44	85
2	44	79
2	54	97
2	44	86
2	37	87
2	43	109
2	57	102
2	62	95
2	55	86
2	46	97
2	41	77
2	48	108
2	54	107
2	55	95
2	44	95
2	41	90
2	43	77
2	37	90
2	58	111
2	44	75
2	55	92
2	43	86
2	57	100
2	41	88
2	56	94
2	48	90
2	34	86
2	50	96
2	41	87
2	46	95
2	41	90
2	31	75
2	37	95
2	41	68
2	66	98
2	48	97
2	58	95
2	46	95
2	66	107
2	55	91
2	46	102
2	32	68
2	59	90
2	56	100
2	59	103
2	57	94
2	59	97
2	46	106
2	59	115
2	44	101
2	57	97
2	45	77
2	50	94
2	39	103
2	37	87
2	43	90
2	55	94
2	43	86
2	48	90
2	52	97
2	46	95
2	50	95
2	59	100
2	56	102
3	41	86
3	50	91
3	62	96
3	37	72
3	56	88
3	50	115
3	50	84
3	52	111
3	52	98
3	52	82
3	55	111
3	30	84
3	48	78
3	54	97
3	48	75
3	56	87
3	55	97
3	46	94
3	66	109
3	52	97
3	48	78
3	54	107
3	54	85
3	52	90
3	60	97
3	34	92
3	36	85
3	50	101
3	60	86
3	30	75
3	50	97
3	60	92
3	60	98
3	50	87
3	58	101
3	52	92
3	57	95
3	46	101
3	54	101
3	66	115
3	50	106
3	59	115




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'AstonUniversity' @ aston.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 & 12 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.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=147312&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.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=147312&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147312&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 time12 seconds
R Server'AstonUniversity' @ aston.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 ~ MWARM30
means87.0985.4476.902

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V
  ~  MWARM30 \tabularnewline
means & 87.098 & 5.447 & 6.902 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147312&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V
  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]87.098[/C][C]5.447[/C][C]6.902[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147312&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147312&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 ~ MWARM30
means87.0985.4476.902







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM3021131.138565.5695.2620.006
Residuals14815908.477107.49

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 2 & 1131.138 & 565.569 & 5.262 & 0.006 \tabularnewline
Residuals & 148 & 15908.477 & 107.49 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147312&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]1131.138[/C][C]565.569[/C][C]5.262[/C][C]0.006[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]15908.477[/C][C]107.49[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147312&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147312&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)
MWARM3021131.138565.5695.2620.006
Residuals14815908.477107.49







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-15.4470.59310.30.024
3-16.9021.51412.2910.008
3-21.456-3.3616.2730.755

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 5.447 & 0.593 & 10.3 & 0.024 \tabularnewline
3-1 & 6.902 & 1.514 & 12.291 & 0.008 \tabularnewline
3-2 & 1.456 & -3.361 & 6.273 & 0.755 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147312&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]5.447[/C][C]0.593[/C][C]10.3[/C][C]0.024[/C][/ROW]
[ROW][C]3-1[/C][C]6.902[/C][C]1.514[/C][C]12.291[/C][C]0.008[/C][/ROW]
[ROW][C]3-2[/C][C]1.456[/C][C]-3.361[/C][C]6.273[/C][C]0.755[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147312&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147312&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
2-15.4470.59310.30.024
3-16.9021.51412.2910.008
3-21.456-3.3616.2730.755







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.8080.448
148

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.808 & 0.448 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147312&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]0.808[/C][C]0.448[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147312&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147312&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)
Group20.8080.448
148



Parameters (Session):
par1 = 3 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 3 ; 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')