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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 computationTue, 08 Dec 2015 15:51:48 +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/2015/Dec/08/t1449589951tj3sc2oqrm5cueo.htm/, Retrieved Thu, 16 May 2024 11:09:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285539, Retrieved Thu, 16 May 2024 11:09:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
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)] [] [2015-12-08 15:51:48] [63a9f0ea7bb98050796b649e85481845] [Current]
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Dataseries X:
0.266482 1
0.33559 1
0.311173 1
0.334147 1
0.234513 1
0.299111 1
0.257682 1
0.183721 1
0.327769 1
0.325996 1
0.391002 1
0.363566 1
0.152813 1
0.254989 1
0.203653 1
0.210185 1
0.239764 1
0.434326 1
0.35787 1
0.340176 1
0.262564 1
0.237622 1
0.262384 1
0.210279 1
0.22089 1
0.236853 1
0.226278 1
0.196102 1
0.279789 1
0.209866 1
0.177551 0
0.173319 0
0.175181 0
0.17854 0
0.163519 0
0.170183 0
0.218037 1
0.196371 1
0.212294 1
0.266892 1
0.201095 1
0.063412 1
0.098648 0
0.158266 0
0.091608 0
0.102083 0
0.127642 0
0.200873 0
0.266392 0
0.264967 0
0.254498 0
0.291954 0
0.220434 0
0.269866 0
0.205558 1
0.221727 1
0.238298 1
0.290024 1
0.262633 1
0.221711 1
0.066994 0
0.086372 0
0.095882 0
0.018689 0
0.056844 0
0.006274 0
0.22685 1
0.20566 1
0.151814 1
0.120956 1
0.15883 1
0.224852 1
0.329066 1
0.306636 1
0.201861 1
0.315074 1
0.341169 1
0.250572 1
0.249494 1
0.265699 1
0.155097 1
0.210458 1
0.146948 1
0.078202 1
0.343073 1
0.315903 1
0.335753 1
0.299549 1
0.299793 1
0.375531 1
0.389232 1
0.207156 1
0.08784 1
0.17352 1
0.188056 1
0.180528 1
0.194627 1
0.265315 1
0.202146 1
0.242861 1
0.260481 1
0.310163 1
0.270641 1
0.089267 1
0.14478 1
0.210279 1
0.18455 1
0.249172 1
0.160686 1
0.278679 1
0.256454 1
0.184378 1
0.212054 1
0.250283 1
0.181701 1
0.261549 1
0.27328 1
0.372114 1
0.393056 1
0.389295 1
0.279933 1
0.281618 1
0.160267 1
0.142466 1
0.143359 1
0.12795 1
0.087165 1
0.115697 1
0.152941 1
0.195976 1
0.20363 1
0.217013 1
0.254909 1
0.178713 1
0.320385 1
0.322044 1
0.300067 1
0.304107 1
0.306014 1
0.23307 1
0.397749 1
0.288917 1
0.310746 1
0.213353 1
0.220617 1
0.345238 1
0.414758 1
0.355736 1
0.335357 1
0.262281 1
0.340256 1
0.450493 1
0.356224 1
0.246404 1
0.175691 1
0.207914 1
0.230532 1
0.303214 1
0.280091 1
0.234196 1
0.259229 1
0.226528 1
0.24275 1
0.184896 1
0.396746 1
0.17227 0
0.176316 0
0.160414 0
0.164529 0
0.073298 0
0.171088 0
0.218885 0
0.192375 0
0.19215 0
0.229298 0
0.197938 0
0.109256 0
0.197919 1
0.182459 1
0.240875 1
0.183218 1
0.216204 1
0.109397 1
0.191576 0
0.206768 0
0.133917 0
0.15331 0
0.116636 0
0.149694 0
0.15989 0
0.121952 0
0.129303 0
0.158453 0
0.207454 0
0.190667 0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ yule.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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285539&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285539&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285539&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 time4 seconds
R Server'George Udny Yule' @ yule.wessa.net







ANOVA Model
spread2 ~ status
means0.160.088

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
spread2  ~  status \tabularnewline
means & 0.16 & 0.088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285539&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]spread2  ~  status[/C][/ROW]
[ROW][C]means[/C][C]0.16[/C][C]0.088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285539&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285539&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
spread2 ~ status
means0.160.088







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
status10.2790.27950.3430
Residuals1931.070.006

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
status & 1 & 0.279 & 0.279 & 50.343 & 0 \tabularnewline
Residuals & 193 & 1.07 & 0.006 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285539&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]status[/C][C]1[/C][C]0.279[/C][C]0.279[/C][C]50.343[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]193[/C][C]1.07[/C][C]0.006[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285539&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285539&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)
status10.2790.27950.3430
Residuals1931.070.006







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.0880.0630.1120

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.088 & 0.063 & 0.112 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285539&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]1-0[/C][C]0.088[/C][C]0.063[/C][C]0.112[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285539&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285539&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
1-00.0880.0630.1120







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group13.4950.063
193

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 3.495 & 0.063 \tabularnewline
  & 193 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285539&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]1[/C][C]3.495[/C][C]0.063[/C][/ROW]
[ROW][C] [/C][C]193[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285539&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285539&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)
Group13.4950.063
193



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