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Description of Statistical Computation

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 computationSun, 10 Nov 2013 14:12:37 -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/2013/Nov/10/t13841107729zlgsaus3wka8tp.htm/, Retrieved Mon, 06 May 2024 14:23:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223773, Retrieved Mon, 06 May 2024 14:23:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80

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)] [One-way ANOVA] [2013-11-07 11:35:04] [de1fe45c170e670168b5ccf4c0f88d1c]
- R  D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-10 19:12:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3	36
6	36
8	56
8	48
7	32
5	44
7	39
8	34
9	41
9	50
3	39
9	62
7	52
9	37
8	50
6	41
7	55
8	41
9	56
7	39
6	52
8	46
7	44
7	48
8	41
9	50
9	50
7	44
4	52
7	54
7	44
9	52
7	37
9	52
10	50
5	36
6	50
9	52
9	55
8	31
6	36
6	49
5	42
8	37
8	41
5	30
6	52
9	30
8	41
4	44
8	66
9	48
7	43
7	57
6	46
9	54
9	48
8	48
4	52
6	62
10	58
8	58
7	62
7	48
8	46
3	34
8	66
10	52
7	55
5	55
10	57
5	56
8	55
9	56
6	54
9	55
8	46
5	52
8	32
3	44
7	46
8	59
10	46
9	46
10	54
9	66
8	56
8	59
8	57
9	52
4	48
6	44
7	41
4	50
9	48
7	48
8	59
8	46
7	54
7	55
9	54
8	59
8	44
9	54
9	52
10	66
7	44
8	57
5	39
9	60
8	45
7	41
8	50
8	39
7	43
6	48
7	37
7	58
6	46
6	43
7	44
9	34
6	30
10	50
4	39
8	37
7	55
10	48
5	39
9	36
8	43
9	50
8	55
8	43
9	60
8	48
9	30
7	43
6	39
8	52
6	39
5	39
3	56
6	59
8	46
7	57
8	50
6	54
9	50
9	60
10	59
7	41
5	48
8	59
9	60
8	56
8	56
4	51

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223773&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223773&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223773&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
V1 ~ V2
means7.2587.56.6675.87.85.67.55657.1676.187.87.46268.2547.3087.8757.4447.2588.333897.3338.75

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
V1  ~  V2 \tabularnewline
means & 7.25 & 8 & 7.5 & 6.667 & 5.8 & 7.8 & 5.6 & 7.556 & 5 & 7.167 & 6.1 & 8 & 7.8 & 7.462 & 6 & 8.25 & 4 & 7.308 & 7.875 & 7.444 & 7.25 & 8 & 8.333 & 8 & 9 & 7.333 & 8.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223773&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]V1  ~  V2[/C][/ROW]
[ROW][C]means[/C][C]7.25[/C][C]8[/C][C]7.5[/C][C]6.667[/C][C]5.8[/C][C]7.8[/C][C]5.6[/C][C]7.556[/C][C]5[/C][C]7.167[/C][C]6.1[/C][C]8[/C][C]7.8[/C][C]7.462[/C][C]6[/C][C]8.25[/C][C]4[/C][C]7.308[/C][C]7.875[/C][C]7.444[/C][C]7.25[/C][C]8[/C][C]8.333[/C][C]8[/C][C]9[/C][C]7.333[/C][C]8.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223773&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223773&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
V1 ~ V2
means7.2587.56.6675.87.85.67.55657.1676.187.87.46268.2547.3087.8757.4447.2588.333897.3338.75






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
V2278667.597321.022128.0560
Residuals131328.4032.507 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
V2 & 27 & 8667.597 & 321.022 & 128.056 & 0 \tabularnewline
Residuals & 131 & 328.403 & 2.507 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223773&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]V2[/C][C]27[/C][C]8667.597[/C][C]321.022[/C][C]128.056[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]131[/C][C]328.403[/C][C]2.507[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223773&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223773&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)
V2278667.597321.022128.0560
Residuals131328.4032.507






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223773&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223773&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223773&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:

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group260.9570.53
131 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 26 & 0.957 & 0.53 \tabularnewline
  & 131 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223773&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]26[/C][C]0.957[/C][C]0.53[/C][/ROW]
[ROW][C] [/C][C]131[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223773&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223773&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)
Group260.9570.53
131


Figures (Output of Computation)

Input Parameters & R Code

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