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Description of Statistical Computation

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 10:36:12 -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/t1322494592gakb28ufduhyfhh.htm/, Retrieved Thu, 31 Oct 2024 23:10:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147819, Retrieved Thu, 31 Oct 2024 23:10:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

Tree of Dependent Computations

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  D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WORKSHOP 8- MC30-...] [2011-11-28 15:17:48] [db177c22332ffa2a0a999e2f71898de2]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WORKSHOP 8- WARMT...] [2011-11-28 15:22:33] [db177c22332ffa2a0a999e2f71898de2]
-                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WORKSHOP 5] [2011-11-28 15:36:12] [68e47018849be3915773eb95b1368c99] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	88
2	94
2	90
2	73
1	68
2	80
2	86
3	86
3	91
1	79
3	96
2	92
3	72
2	96
1	70
1	86
2	87
3	88
2	79
1	90
2	95
2	85
2	90
3	115
3	84
2	79
1	94
2	97
2	86
3	111
3	87
3	98
3	87
1	68
1	88
3	82
3	111
2	75
1	94
1	95
1	80
8	95
2	68
1	94
1	88
3	84
1	101
2	98
3	78
1	109
1	102
1	81
3	97
3	75
2	97
1	101
3	101
2	95
1	95
2	95
1	90
2	107
3	92
1	86
1	70
3	95
1	96
2	91
3	87
1	92
3	97
2	102
1	91
2	68
1	88
2	97
2	90
3	101
3	94
3	101
3	109
2	100
2	103
2	94
3	97
1	85
1	75
2	77
1	87
3	78
3	108
2	97
2	106
2	107
2	95
3	107
2	115
2	101
3	85
3	90
3	115
2	95
2	97
1	112
3	97
2	77
2	90
2	94
2	103
2	77
1	98
2	90
2	111
1	77
1	88
2	75
3	92
1	78
3	106
1	80
2	87
2	92
1	86
3	85
2	90
3	101
2	94
2	86
3	86
2	90
3	75
2	86
1	91
2	97
1	91
1	70
3	98
1	96
2	95
2	100
2	95
1	97
3	97
3	92
3	115
2	88
1	87
2	100
3	98
2	102
1	96

Tables (Output of Computation)





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
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147819&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]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147819&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147819&T=0

As an alternative you can also use a QR Code:  
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
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






ANOVA Model
WISCRY7V ~ MCVRBIQ
means88.1363.6346.1086.864

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MCVRBIQ \tabularnewline
means & 88.136 & 3.634 & 6.108 & 6.864 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147819&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MCVRBIQ[/C][/ROW]
[ROW][C]means[/C][C]88.136[/C][C]3.634[/C][C]6.108[/C][C]6.864[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147819&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147819&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Model
WISCRY7V ~ MCVRBIQ
means88.1363.6346.1086.864






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MCVRBIQ3853.336284.4452.5830.056
Residuals14716186.28110.111 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MCVRBIQ & 3 & 853.336 & 284.445 & 2.583 & 0.056 \tabularnewline
Residuals & 147 & 16186.28 & 110.111 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147819&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]MCVRBIQ[/C][C]3[/C][C]853.336[/C][C]284.445[/C][C]2.583[/C][C]0.056[/C][/ROW]
[ROW][C]Residuals[/C][C]147[/C][C]16186.28[/C][C]110.111[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147819&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147819&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MCVRBIQ3853.336284.4452.5830.056
Residuals14716186.28110.111






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-13.634-1.7599.0280.301
3-16.1080.32711.8890.034
8-16.864-20.71334.440.917
3-22.474-2.8857.8320.628
8-23.23-24.26230.7210.99
8-30.756-26.81428.3261

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 3.634 & -1.759 & 9.028 & 0.301 \tabularnewline
3-1 & 6.108 & 0.327 & 11.889 & 0.034 \tabularnewline
8-1 & 6.864 & -20.713 & 34.44 & 0.917 \tabularnewline
3-2 & 2.474 & -2.885 & 7.832 & 0.628 \tabularnewline
8-2 & 3.23 & -24.262 & 30.721 & 0.99 \tabularnewline
8-3 & 0.756 & -26.814 & 28.326 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147819&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]3.634[/C][C]-1.759[/C][C]9.028[/C][C]0.301[/C][/ROW]
[ROW][C]3-1[/C][C]6.108[/C][C]0.327[/C][C]11.889[/C][C]0.034[/C][/ROW]
[ROW][C]8-1[/C][C]6.864[/C][C]-20.713[/C][C]34.44[/C][C]0.917[/C][/ROW]
[ROW][C]3-2[/C][C]2.474[/C][C]-2.885[/C][C]7.832[/C][C]0.628[/C][/ROW]
[ROW][C]8-2[/C][C]3.23[/C][C]-24.262[/C][C]30.721[/C][C]0.99[/C][/ROW]
[ROW][C]8-3[/C][C]0.756[/C][C]-26.814[/C][C]28.326[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147819&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147819&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-13.634-1.7599.0280.301
3-16.1080.32711.8890.034
8-16.864-20.71334.440.917
3-22.474-2.8857.8320.628
8-23.23-24.26230.7210.99
8-30.756-26.81428.3261






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.8780.454
147 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.878 & 0.454 \tabularnewline
  & 147 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147819&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]3[/C][C]0.878[/C][C]0.454[/C][/ROW]
[ROW][C] [/C][C]147[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147819&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147819&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.8780.454
147


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; 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')