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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 computationThu, 13 Nov 2014 17:11:28 +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/Nov/13/t1415898699h6mdn4q5m13oix8.htm/, Retrieved Sun, 19 May 2024 10:47:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=254500, Retrieved Sun, 19 May 2024 10:47:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact70

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)] [] [2014-11-13 17:11:28] [5dcf1481ccfcf5c49234bf13d276444c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	36
1	36
2	56
2	48
2	32
1	44
2	39
2	34
3	41
3	50
1	39
3	62
2	52
3	37
2	50
1	41
2	55
2	41
3	56
2	39
1	52
2	46
2	44
2	48
2	41
3	50
3	50
2	44
1	52
2	54
2	44
3	52
2	37
3	52
3	50
1	36
1	50
3	52
3	55
2	31
1	36
1	49
1	42
2	37
2	41
1	30
1	52
3	30
2	41
1	44
2	66
3	48
2	43
2	57
1	46
3	54
3	48
2	48
1	52
1	62
3	58
2	58
2	62
2	48
2	46
1	34
2	66
3	52
2	55
1	55
3	57
1	56
2	55
3	56
1	54
3	55
2	46
1	52
2	32
1	44
2	46
2	59
3	46
3	46
3	54
3	66
2	56
2	59
2	57
3	52
1	48
1	44
2	41
1	50
3	48
2	48
2	59
2	46
2	54
2	55
3	54
2	59
2	44
3	54
3	52
3	66
2	44
2	57
1	39
3	60
2	45
2	41
2	50
2	39
2	43
1	48
2	37
2	58
1	46
1	43
2	44
3	34
1	30
3	50
1	39
2	37
2	55
3	48
1	39
3	36
2	43
3	50
2	55
2	43
3	60
2	48
3	30
2	43
1	39
2	52
1	39
1	39
1	56
1	59
2	46
2	57
2	50
2	54
3	50
3	60
3	59
2	41
1	48
2	59
3	60
2	56
2	56
1	51

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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254500&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254500&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 Ronald Aylmer Fisher' @ fisher.wessa.net






ANOVA Model
ChildIQ ~ MaternalWarmth
means45.1463.1246.016

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
ChildIQ  ~  MaternalWarmth \tabularnewline
means & 45.146 & 3.124 & 6.016 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254500&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]ChildIQ  ~  MaternalWarmth[/C][/ROW]
[ROW][C]means[/C][C]45.146[/C][C]3.124[/C][C]6.016[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254500&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
ChildIQ ~ MaternalWarmth
means45.1463.1246.016






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MaternalWarmth2759.796379.8985.6590.004
Residuals15510405.57767.133 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MaternalWarmth & 2 & 759.796 & 379.898 & 5.659 & 0.004 \tabularnewline
Residuals & 155 & 10405.577 & 67.133 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254500&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]MaternalWarmth[/C][C]2[/C][C]759.796[/C][C]379.898[/C][C]5.659[/C][C]0.004[/C][/ROW]
[ROW][C]Residuals[/C][C]155[/C][C]10405.577[/C][C]67.133[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254500&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254500&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)
MaternalWarmth2759.796379.8985.6590.004
Residuals15510405.57767.133






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-13.124-0.6516.8990.126
3-16.0161.78410.2490.003
3-22.893-0.8256.610.16

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 3.124 & -0.651 & 6.899 & 0.126 \tabularnewline
3-1 & 6.016 & 1.784 & 10.249 & 0.003 \tabularnewline
3-2 & 2.893 & -0.825 & 6.61 & 0.16 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254500&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]3.124[/C][C]-0.651[/C][C]6.899[/C][C]0.126[/C][/ROW]
[ROW][C]3-1[/C][C]6.016[/C][C]1.784[/C][C]10.249[/C][C]0.003[/C][/ROW]
[ROW][C]3-2[/C][C]2.893[/C][C]-0.825[/C][C]6.61[/C][C]0.16[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254500&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254500&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
2-13.124-0.6516.8990.126
3-16.0161.78410.2490.003
3-22.893-0.8256.610.16






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.5710.566
155 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.571 & 0.566 \tabularnewline
  & 155 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254500&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]0.571[/C][C]0.566[/C][/ROW]
[ROW][C] [/C][C]155[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254500&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254500&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)
Group20.5710.566
155


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; 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){
'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')