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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 computationSun, 14 Dec 2014 17:06:05 +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/2014/Dec/14/t1418576846jm5kt3htr082l9w.htm/, Retrieved Thu, 16 May 2024 16:10:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267754, Retrieved Thu, 16 May 2024 16:10:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA] [2014-10-24 21:12:01] [5c51c91cab622bcf955f01721b682696]
- R PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA Intr.M] [2014-12-14 17:06:05] [56a3e0974002d1c8d48b4dd203e70051] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2011 26
2011 51
2011 57
2011 37
2011 67
2011 43
2011 52
2011 52
2011 43
2011 84
2011 67
2011 49
2011 70
2011 52
2011 58
2011 68
2011 62
2011 43
2011 56
2011 56
2011 74
2011 63
2011 58
2011 57
2011 63
2011 53
2011 57
2011 51
2011 64
2011 53
2011 29
2011 54
2011 58
2011 43
2011 51
2011 53
2011 54
2011 56
2011 61
2011 47
2011 39
2011 48
2011 50
2011 35
2011 30
2011 68
2011 49
2011 61
2011 67
2011 47
2011 56
2011 50
2011 43
2011 67
2011 62
2011 57
2011 41
2011 54
2011 45
2011 48
2011 61
2011 56
2011 41
2011 43
2011 53
2011 44
2011 66
2011 58
2011 46
2011 37
2011 51
2011 51
2011 56
2011 66
2011 45
2011 37
2011 59
2011 42
2011 38
2011 66
2011 34
2011 53
2011 49
2011 55
2011 49
2011 59
2011 40
2011 58
2011 60
2011 63
2011 56
2011 54
2011 52
2011 34
2011 69
2011 32
2011 48
2011 67
2011 58
2011 57
2011 42
2011 64
2011 58
2011 66
2011 26
2011 61
2011 52
2011 51
2011 55
2011 50
2011 60
2011 56
2011 63
2011 61
2012 52
2012 16
2012 46
2012 56
2012 52
2012 55
2012 50
2012 59
2012 60
2012 52
2012 44
2012 67
2012 52
2012 55
2012 37
2012 54
2012 72
2012 51
2012 48
2012 60
2012 50
2012 63
2012 33
2012 67
2012 46
2012 54
2012 59
2012 61
2012 33
2012 47
2012 69
2012 52
2012 55
2012 55
2012 41
2012 73
2012 51
2012 52
2012 50
2012 51
2012 60
2012 56
2012 56
2012 29
2012 66
2012 66
2012 73
2012 55
2012 64
2012 40
2012 46
2012 58
2012 43
2012 61
2012 51
2012 50
2012 52
2012 54
2012 66
2012 61
2012 80
2012 51
2012 56
2012 56
2012 56
2012 53
2012 47
2012 25
2012 47
2012 46
2012 50
2012 39
2012 51
2012 58
2012 35
2012 58
2012 60
2012 62
2012 63
2012 53
2012 46
2012 67
2012 59
2012 64
2012 38
2012 50
2012 48
2012 48
2012 47
2012 66
2012 47
2012 63
2012 58
2012 44
2012 51
2012 43
2012 55
2012 38
2012 56
2012 45
2012 50
2012 54
2012 57
2012 60
2012 55
2012 56
2012 49
2012 37
2012 43
2012 59
2012 46
2012 51
2012 58
2012 64
2012 53
2012 48
2012 51
2012 47
2012 59
2012 62
2012 62
2012 51
2012 64
2012 52
2012 67
2012 50
2012 54
2012 58
2012 56
2012 63
2012 31
2012 65
2012 71
2012 50
2012 57
2012 47
2012 54
2012 47
2012 57
2012 43
2012 41
2012 63
2012 63
2012 56
2012 51
2012 50
2012 22
2012 41
2012 59
2012 56
2012 66
2012 53
2012 42
2012 52
2012 54
2012 44
2012 62
2012 53
2012 50
2012 36
2012 76
2012 66
2012 62
2012 59
2012 47
2012 55
2012 58
2012 60
2012 44
2012 57
2012 45
2014 58
2014 51
2014 57
2014 30
2014 46
2014 51
2014 56
2014 58
2014 44
2014 14
2014 53
2014 42
2014 49
2014 44
2014 62
2014 30
2014 46
2014 56
2014 50
2014 54
2014 48
2014 55
2014 35
2014 55
2014 41
2014 59
2014 54
2014 66
2014 55
2014 45
2014 51
2014 47
2014 42
2014 53
2014 53
2014 41
2014 55
2014 55
2014 46
2014 63
2014 43
2014 65
2014 59
2014 39
2014 44
2014 60
2014 57
2014 67
2014 52
2014 52
2014 69
2014 46
2014 46
2014 53
2014 40
2014 70
2014 54
2014 77
2014 45
2014 60
2014 47
2014 50
2014 66
2014 60
2014 41
2014 53
2014 34
2014 51
2014 69
2014 60
2014 45
2014 58
2014 39
2014 51
2014 52
2014 49
2014 63
2014 44
2014 51
2014 52
2014 60
2014 53
2014 53
2014 52
2014 31
2014 51
2014 65
2014 51
2014 49
2014 61
2014 58
2014 62
2014 54
2014 52
2014 72
2014 50
2014 65
2014 53
2014 56
2014 63
2014 62
2014 66
2014 50
2014 45
2014 58
2014 52
2014 53
2014 68
2014 59
2014 58
2014 52
2014 45
2014 58
2014 70
2014 69
2014 71
2014 46
2014 58
2014 39
2014 46
2014 64
2014 67
2014 44
2014 54
2014 41
2014 68
2014 63
2014 57
2014 61
2014 39
2014 69
2014 64
2014 38
2014 59
2014 51
2014 59
2014 51
2014 65
2014 47
2014 50
2014 57
2014 21
2014 47
2014 51
2014 37
2014 67
2014 43
2014 58
2014 51
2014 40
2014 41
2014 58
2014 64
2014 64
2014 58
2014 50
2014 59
2014 55
2014 59
2014 58
2014 41
2014 56
2014 63
2014 77
2014 60
2014 58
2014 64
2014 47
2014 46
2014 62
2014 60
2014 50
2014 46
2014 44
2014 58
2014 56
2014 43
2014 54
2014 54
2014 56
2014 65
2014 66
2014 62
2014 58
2014 67
2014 25
2014 56
2014 53
2014 56
2014 59
2014 46
2014 49
2014 56
2014 76
2014 33
2014 49
2014 53
2014 58
2014 72
2014 51
2014 42
2014 69
2014 51
2014 54
2014 52
2014 59
2014 51
2014 67
2014 64
2014 58
2014 53

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'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267754&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267754&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'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
AMS.I ~ Year
means52.9560.1840.66

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
AMS.I  ~  Year \tabularnewline
means & 52.956 & 0.184 & 0.66 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267754&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]AMS.I  ~  Year[/C][/ROW]
[ROW][C]means[/C][C]52.956[/C][C]0.184[/C][C]0.66[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267754&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
AMS.I ~ Year
means52.9560.1840.66






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Year238.92219.4610.1890.828
Residuals49350653.317102.745 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Year & 2 & 38.922 & 19.461 & 0.189 & 0.828 \tabularnewline
Residuals & 493 & 50653.317 & 102.745 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267754&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]Year[/C][C]2[/C][C]38.922[/C][C]19.461[/C][C]0.189[/C][C]0.828[/C][/ROW]
[ROW][C]Residuals[/C][C]493[/C][C]50653.317[/C][C]102.745[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267754&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267754&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)
Year238.92219.4610.1890.828
Residuals49350653.317102.745






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2012-20110.184-2.6973.0650.988
2014-20110.66-2.113.430.841
2014-20120.476-1.9762.9280.892

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2012-2011 & 0.184 & -2.697 & 3.065 & 0.988 \tabularnewline
2014-2011 & 0.66 & -2.11 & 3.43 & 0.841 \tabularnewline
2014-2012 & 0.476 & -1.976 & 2.928 & 0.892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267754&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]2012-2011[/C][C]0.184[/C][C]-2.697[/C][C]3.065[/C][C]0.988[/C][/ROW]
[ROW][C]2014-2011[/C][C]0.66[/C][C]-2.11[/C][C]3.43[/C][C]0.841[/C][/ROW]
[ROW][C]2014-2012[/C][C]0.476[/C][C]-1.976[/C][C]2.928[/C][C]0.892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267754&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267754&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
2012-20110.184-2.6973.0650.988
2014-20110.66-2.113.430.841
2014-20120.476-1.9762.9280.892






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.50.607
493 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.5 & 0.607 \tabularnewline
  & 493 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267754&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]0.5[/C][C]0.607[/C][/ROW]
[ROW][C] [/C][C]493[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267754&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267754&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)
Group20.50.607
493


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
R code (references can be found in the software module):
par3 <- 'FALSE'
par2 <- '1'
par1 <- '2'
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){
'Tukey Plot'
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<-leveneTest(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')