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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, 08 Mar 2020 19:39:07 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Mar/08/t1583697681cx7w9r8r9t14tdz.htm/, Retrieved Fri, 29 Mar 2024 12:46:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319090, Retrieved Fri, 29 Mar 2024 12:46:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
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)] [IgA] [2020-03-08 18:39:07] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
641.03	"A"
2451.92	"A"
1554.49	"A"
2403.85	"A"
2099.36	"A"
625.00	"A"
1378.21	"A"
2227.56	"B"
3477.56	"B"
1346.15	"B"
4615.38	"B"
2948.72	"B"
3814.10	"B"
592.95	"B"
1554.49	"B"
6266.03	"C"
6201.92	"C"
3108.97	"C"
5769.23	"C"
3317.31	"C"
961.54	"C"
1041.67	"C"
929.49	"D"
1810.90	"D"
1474.36	"D"
2740.38	"D"
7371.79	"D"
2740.38	"D"
6057.69	"D"
1698.72	"D"




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319090&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319090&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319090&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Response ~ Treatment
means1593.409978.7052216.1161509.555

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response  ~  Treatment \tabularnewline
means & 1593.409 & 978.705 & 2216.116 & 1509.555 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319090&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]1593.409[/C][C]978.705[/C][C]2216.116[/C][C]1509.555[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319090&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319090&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
Response ~ Treatment
means1593.409978.7052216.1161509.555







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment318454548.2836151516.0941.8360.165
Residuals2687133386.2473351284.086

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 3 & 18454548.283 & 6151516.094 & 1.836 & 0.165 \tabularnewline
Residuals & 26 & 87133386.247 & 3351284.086 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319090&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]Treatment[/C][C]3[/C][C]18454548.283[/C][C]6151516.094[/C][C]1.836[/C][C]0.165[/C][/ROW]
[ROW][C]Residuals[/C][C]26[/C][C]87133386.247[/C][C]3351284.086[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319090&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319090&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)
Treatment318454548.2836151516.0941.8360.165
Residuals2687133386.2473351284.086







Tukey Honest Significant Difference Comparisons
difflwruprp adj
B-A978.705-1620.4593577.8690.732
C-A2216.116-468.2894900.5210.133
D-A1509.555-1089.6094108.7190.4
C-B1237.411-1361.7533836.5750.567
D-B530.85-1980.1813041.8810.937
D-C-706.561-3305.7251892.6030.878

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
B-A & 978.705 & -1620.459 & 3577.869 & 0.732 \tabularnewline
C-A & 2216.116 & -468.289 & 4900.521 & 0.133 \tabularnewline
D-A & 1509.555 & -1089.609 & 4108.719 & 0.4 \tabularnewline
C-B & 1237.411 & -1361.753 & 3836.575 & 0.567 \tabularnewline
D-B & 530.85 & -1980.181 & 3041.881 & 0.937 \tabularnewline
D-C & -706.561 & -3305.725 & 1892.603 & 0.878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319090&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]B-A[/C][C]978.705[/C][C]-1620.459[/C][C]3577.869[/C][C]0.732[/C][/ROW]
[ROW][C]C-A[/C][C]2216.116[/C][C]-468.289[/C][C]4900.521[/C][C]0.133[/C][/ROW]
[ROW][C]D-A[/C][C]1509.555[/C][C]-1089.609[/C][C]4108.719[/C][C]0.4[/C][/ROW]
[ROW][C]C-B[/C][C]1237.411[/C][C]-1361.753[/C][C]3836.575[/C][C]0.567[/C][/ROW]
[ROW][C]D-B[/C][C]530.85[/C][C]-1980.181[/C][C]3041.881[/C][C]0.937[/C][/ROW]
[ROW][C]D-C[/C][C]-706.561[/C][C]-3305.725[/C][C]1892.603[/C][C]0.878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319090&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319090&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
B-A978.705-1620.4593577.8690.732
C-A2216.116-468.2894900.5210.133
D-A1509.555-1089.6094108.7190.4
C-B1237.411-1361.7533836.5750.567
D-B530.85-1980.1813041.8810.937
D-C-706.561-3305.7251892.6030.878







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group31.6170.21
26

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 1.617 & 0.21 \tabularnewline
  & 26 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319090&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]3[/C][C]1.617[/C][C]0.21[/C][/ROW]
[ROW][C] [/C][C]26[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319090&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319090&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)
Group31.6170.21
26



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')