Free Statistics

of Irreproducible Research!

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, 15 Dec 2014 13:58:38 +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/15/t1418651925uw5unzunbstc8va.htm/, Retrieved Thu, 31 Oct 2024 23:56:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268414, Retrieved Thu, 31 Oct 2024 23:56:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
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)] [] [2014-12-15 13:58:38] [58179e1d3a5a39b9daf58e365d8a3352] [Current]
Feedback Forum

Post a new message
Dataseries X:
21 12.9
21 12.8
21 7.4
21 6.7
21 12.6
21 14.8
23 13.3
22 11.1
25 8.2
21 11.4
23 6.4
21 12
21 6.3
25 11.3
21 11.9
21 9.3
24 10
21 13.8
24 10.8
21 11.7
22 10.9
20 16.1
21 9.9
22 11.5
22 8.3
21 11.7
21 9
22 10.8
20 10.4
21 12.7
21 11.8
24 13
22 10.8
22 12.3
21 11.3
20 11.6
23 10.9
20 12.1
23 13.3
21 10.1
21 14.3
22 9.3
21 12.5
21 7.6
21 9.2
22 14.5
21 12.3
21 12.6
21 13
21 12.6
20 13.2
21 7.7
19 10.5
19 10.9
20 4.3
19 10.3
20 11.4
21 5.6
18 8.8
21 9
20 9.6
21 6.4
19 11.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268414&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268414&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268414&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







ANOVA Model
TOT ~ age
means8.82.0252.2871.9162.2562.1752.4670.95

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
TOT  ~  age \tabularnewline
means & 8.8 & 2.025 & 2.287 & 1.916 & 2.256 & 2.175 & 2.467 & 0.95 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268414&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]TOT  ~  age[/C][/ROW]
[ROW][C]means[/C][C]8.8[/C][C]2.025[/C][C]2.287[/C][C]1.916[/C][C]2.256[/C][C]2.175[/C][C]2.467[/C][C]0.95[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268414&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268414&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
TOT ~ age
means8.82.0252.2871.9162.2562.1752.4670.95







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
age78.461.2090.1910.986
Residuals55348.626.339

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
age & 7 & 8.46 & 1.209 & 0.191 & 0.986 \tabularnewline
Residuals & 55 & 348.62 & 6.339 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268414&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]age[/C][C]7[/C][C]8.46[/C][C]1.209[/C][C]0.191[/C][C]0.986[/C][/ROW]
[ROW][C]Residuals[/C][C]55[/C][C]348.62[/C][C]6.339[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268414&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268414&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)
age78.461.2090.1910.986
Residuals55348.626.339







Tukey Honest Significant Difference Comparisons
difflwruprp adj
19-182.025-6.84310.8930.996
20-182.287-6.12510.70.989
21-181.916-6.1399.970.995
22-182.256-6.10510.6160.989
23-182.175-6.69311.0430.994
24-182.467-6.69211.6250.989
25-180.95-8.76410.6641
20-190.263-4.5955.121
21-19-0.109-4.3164.0971
22-190.231-4.5364.9971
23-190.15-5.4595.7591
24-190.442-5.6166.51
25-19-1.075-7.9445.7941
21-20-0.372-3.5072.7631
22-20-0.032-3.8863.8221
23-20-0.113-4.974.7451
24-200.179-5.1915.5491
25-20-1.338-7.6084.9330.997
22-210.34-2.6533.3331
23-210.259-3.9474.4661
24-210.551-4.2385.341
25-21-0.966-6.7474.8160.999
23-22-0.081-4.8474.6861
24-220.211-5.0775.4991
25-22-1.306-7.5064.8950.998
24-230.292-5.7666.351
25-23-1.225-8.0945.6440.999
25-24-1.517-8.7575.7240.998

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
19-18 & 2.025 & -6.843 & 10.893 & 0.996 \tabularnewline
20-18 & 2.287 & -6.125 & 10.7 & 0.989 \tabularnewline
21-18 & 1.916 & -6.139 & 9.97 & 0.995 \tabularnewline
22-18 & 2.256 & -6.105 & 10.616 & 0.989 \tabularnewline
23-18 & 2.175 & -6.693 & 11.043 & 0.994 \tabularnewline
24-18 & 2.467 & -6.692 & 11.625 & 0.989 \tabularnewline
25-18 & 0.95 & -8.764 & 10.664 & 1 \tabularnewline
20-19 & 0.263 & -4.595 & 5.12 & 1 \tabularnewline
21-19 & -0.109 & -4.316 & 4.097 & 1 \tabularnewline
22-19 & 0.231 & -4.536 & 4.997 & 1 \tabularnewline
23-19 & 0.15 & -5.459 & 5.759 & 1 \tabularnewline
24-19 & 0.442 & -5.616 & 6.5 & 1 \tabularnewline
25-19 & -1.075 & -7.944 & 5.794 & 1 \tabularnewline
21-20 & -0.372 & -3.507 & 2.763 & 1 \tabularnewline
22-20 & -0.032 & -3.886 & 3.822 & 1 \tabularnewline
23-20 & -0.113 & -4.97 & 4.745 & 1 \tabularnewline
24-20 & 0.179 & -5.191 & 5.549 & 1 \tabularnewline
25-20 & -1.338 & -7.608 & 4.933 & 0.997 \tabularnewline
22-21 & 0.34 & -2.653 & 3.333 & 1 \tabularnewline
23-21 & 0.259 & -3.947 & 4.466 & 1 \tabularnewline
24-21 & 0.551 & -4.238 & 5.34 & 1 \tabularnewline
25-21 & -0.966 & -6.747 & 4.816 & 0.999 \tabularnewline
23-22 & -0.081 & -4.847 & 4.686 & 1 \tabularnewline
24-22 & 0.211 & -5.077 & 5.499 & 1 \tabularnewline
25-22 & -1.306 & -7.506 & 4.895 & 0.998 \tabularnewline
24-23 & 0.292 & -5.766 & 6.35 & 1 \tabularnewline
25-23 & -1.225 & -8.094 & 5.644 & 0.999 \tabularnewline
25-24 & -1.517 & -8.757 & 5.724 & 0.998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268414&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]19-18[/C][C]2.025[/C][C]-6.843[/C][C]10.893[/C][C]0.996[/C][/ROW]
[ROW][C]20-18[/C][C]2.287[/C][C]-6.125[/C][C]10.7[/C][C]0.989[/C][/ROW]
[ROW][C]21-18[/C][C]1.916[/C][C]-6.139[/C][C]9.97[/C][C]0.995[/C][/ROW]
[ROW][C]22-18[/C][C]2.256[/C][C]-6.105[/C][C]10.616[/C][C]0.989[/C][/ROW]
[ROW][C]23-18[/C][C]2.175[/C][C]-6.693[/C][C]11.043[/C][C]0.994[/C][/ROW]
[ROW][C]24-18[/C][C]2.467[/C][C]-6.692[/C][C]11.625[/C][C]0.989[/C][/ROW]
[ROW][C]25-18[/C][C]0.95[/C][C]-8.764[/C][C]10.664[/C][C]1[/C][/ROW]
[ROW][C]20-19[/C][C]0.263[/C][C]-4.595[/C][C]5.12[/C][C]1[/C][/ROW]
[ROW][C]21-19[/C][C]-0.109[/C][C]-4.316[/C][C]4.097[/C][C]1[/C][/ROW]
[ROW][C]22-19[/C][C]0.231[/C][C]-4.536[/C][C]4.997[/C][C]1[/C][/ROW]
[ROW][C]23-19[/C][C]0.15[/C][C]-5.459[/C][C]5.759[/C][C]1[/C][/ROW]
[ROW][C]24-19[/C][C]0.442[/C][C]-5.616[/C][C]6.5[/C][C]1[/C][/ROW]
[ROW][C]25-19[/C][C]-1.075[/C][C]-7.944[/C][C]5.794[/C][C]1[/C][/ROW]
[ROW][C]21-20[/C][C]-0.372[/C][C]-3.507[/C][C]2.763[/C][C]1[/C][/ROW]
[ROW][C]22-20[/C][C]-0.032[/C][C]-3.886[/C][C]3.822[/C][C]1[/C][/ROW]
[ROW][C]23-20[/C][C]-0.113[/C][C]-4.97[/C][C]4.745[/C][C]1[/C][/ROW]
[ROW][C]24-20[/C][C]0.179[/C][C]-5.191[/C][C]5.549[/C][C]1[/C][/ROW]
[ROW][C]25-20[/C][C]-1.338[/C][C]-7.608[/C][C]4.933[/C][C]0.997[/C][/ROW]
[ROW][C]22-21[/C][C]0.34[/C][C]-2.653[/C][C]3.333[/C][C]1[/C][/ROW]
[ROW][C]23-21[/C][C]0.259[/C][C]-3.947[/C][C]4.466[/C][C]1[/C][/ROW]
[ROW][C]24-21[/C][C]0.551[/C][C]-4.238[/C][C]5.34[/C][C]1[/C][/ROW]
[ROW][C]25-21[/C][C]-0.966[/C][C]-6.747[/C][C]4.816[/C][C]0.999[/C][/ROW]
[ROW][C]23-22[/C][C]-0.081[/C][C]-4.847[/C][C]4.686[/C][C]1[/C][/ROW]
[ROW][C]24-22[/C][C]0.211[/C][C]-5.077[/C][C]5.499[/C][C]1[/C][/ROW]
[ROW][C]25-22[/C][C]-1.306[/C][C]-7.506[/C][C]4.895[/C][C]0.998[/C][/ROW]
[ROW][C]24-23[/C][C]0.292[/C][C]-5.766[/C][C]6.35[/C][C]1[/C][/ROW]
[ROW][C]25-23[/C][C]-1.225[/C][C]-8.094[/C][C]5.644[/C][C]0.999[/C][/ROW]
[ROW][C]25-24[/C][C]-1.517[/C][C]-8.757[/C][C]5.724[/C][C]0.998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268414&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268414&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
19-182.025-6.84310.8930.996
20-182.287-6.12510.70.989
21-181.916-6.1399.970.995
22-182.256-6.10510.6160.989
23-182.175-6.69311.0430.994
24-182.467-6.69211.6250.989
25-180.95-8.76410.6641
20-190.263-4.5955.121
21-19-0.109-4.3164.0971
22-190.231-4.5364.9971
23-190.15-5.4595.7591
24-190.442-5.6166.51
25-19-1.075-7.9445.7941
21-20-0.372-3.5072.7631
22-20-0.032-3.8863.8221
23-20-0.113-4.974.7451
24-200.179-5.1915.5491
25-20-1.338-7.6084.9330.997
22-210.34-2.6533.3331
23-210.259-3.9474.4661
24-210.551-4.2385.341
25-21-0.966-6.7474.8160.999
23-22-0.081-4.8474.6861
24-220.211-5.0775.4991
25-22-1.306-7.5064.8950.998
24-230.292-5.7666.351
25-23-1.225-8.0945.6440.999
25-24-1.517-8.7575.7240.998







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group70.9490.477
55

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 0.949 & 0.477 \tabularnewline
  & 55 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268414&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]7[/C][C]0.949[/C][C]0.477[/C][/ROW]
[ROW][C] [/C][C]55[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268414&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268414&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)
Group70.9490.477
55



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')