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 computationSun, 09 Dec 2012 11:23:27 -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/2012/Dec/09/t1355070298n13pznyqa6wcx34.htm/, Retrieved Thu, 28 Mar 2024 18:56:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197972, Retrieved Thu, 28 Mar 2024 18:56:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
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)] [] [2010-11-01 13:37:53] [b98453cac15ba1066b407e146608df68]
- R  D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Paper One-way Anova] [2012-12-09 16:23:27] [c63d55528b56cf8bb48e0b5d1a959d8e] [Current]
Feedback Forum

Post a new message
Dataseries X:
89	'E'
89	'E'
70	'E'
69	'E'
65	'E'
64	'E'
56	'E'
52	'E'
52	'E'
47	'E'
47	'E'
47	'E'
45	'E'
45	'E'
43	'E'
38	'E'
37	'E'
36	'E'
31	'E'
25	'E'
84	'I'
80	'I'
64	'I'
62	'I'
61	'I'
58	'I'
56	'I'
56	'I'
51	'I'
49	'I'
48	'I'
46	'I'
46	'I'
44	'I'
43	'I'
43	'I'
42	'I'
36	'I'
32	'I'
22	'I'
82	'F'
79	'F'
74	'F'
64	'F'
61	'F'
60	'F'
57	'F'
56	'F'
50	'F'
48	'F'
45	'F'
43	'F'
42	'F'
42	'F'
41	'F'
41	'F'
39	'F'
38	'F'
36	'F'
34	'F'
100	'S'
91	'S'
61	'S'
58	'S'
56	'S'
55	'S'
54	'S'
52	'S'
50	'S'
49	'S'
47	'S'
47	'S'
47	'S'
46	'S'
43	'S'
43	'S'
42	'S'
41	'S'
37	'S'
27	'S'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197972&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197972&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197972&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'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
punten ~ landen
means52.35-0.75-1.2-0.05

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
punten  ~  landen \tabularnewline
means & 52.35 & -0.75 & -1.2 & -0.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197972&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]punten  ~  landen[/C][/ROW]
[ROW][C]means[/C][C]52.35[/C][C]-0.75[/C][C]-1.2[/C][C]-0.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197972&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197972&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
punten ~ landen
means52.35-0.75-1.2-0.05







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
landen320.16.70.0260.994
Residuals7619248.1253.264

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
landen & 3 & 20.1 & 6.7 & 0.026 & 0.994 \tabularnewline
Residuals & 76 & 19248.1 & 253.264 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197972&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]landen[/C][C]3[/C][C]20.1[/C][C]6.7[/C][C]0.026[/C][C]0.994[/C][/ROW]
[ROW][C]Residuals[/C][C]76[/C][C]19248.1[/C][C]253.264[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197972&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197972&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)
landen320.16.70.0260.994
Residuals7619248.1253.264







Tukey Honest Significant Difference Comparisons
difflwruprp adj
F-E-0.75-13.96912.4690.999
I-E-1.2-14.41912.0190.995
S-E-0.05-13.26913.1691
I-F-0.45-13.66912.7691
S-F0.7-12.51913.9190.999
S-I1.15-12.06914.3690.996

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
F-E & -0.75 & -13.969 & 12.469 & 0.999 \tabularnewline
I-E & -1.2 & -14.419 & 12.019 & 0.995 \tabularnewline
S-E & -0.05 & -13.269 & 13.169 & 1 \tabularnewline
I-F & -0.45 & -13.669 & 12.769 & 1 \tabularnewline
S-F & 0.7 & -12.519 & 13.919 & 0.999 \tabularnewline
S-I & 1.15 & -12.069 & 14.369 & 0.996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197972&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]F-E[/C][C]-0.75[/C][C]-13.969[/C][C]12.469[/C][C]0.999[/C][/ROW]
[ROW][C]I-E[/C][C]-1.2[/C][C]-14.419[/C][C]12.019[/C][C]0.995[/C][/ROW]
[ROW][C]S-E[/C][C]-0.05[/C][C]-13.269[/C][C]13.169[/C][C]1[/C][/ROW]
[ROW][C]I-F[/C][C]-0.45[/C][C]-13.669[/C][C]12.769[/C][C]1[/C][/ROW]
[ROW][C]S-F[/C][C]0.7[/C][C]-12.519[/C][C]13.919[/C][C]0.999[/C][/ROW]
[ROW][C]S-I[/C][C]1.15[/C][C]-12.069[/C][C]14.369[/C][C]0.996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197972&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197972&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
F-E-0.75-13.96912.4690.999
I-E-1.2-14.41912.0190.995
S-E-0.05-13.26913.1691
I-F-0.45-13.66912.7691
S-F0.7-12.51913.9190.999
S-I1.15-12.06914.3690.996







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.1870.905
76

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.187 & 0.905 \tabularnewline
  & 76 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197972&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]0.187[/C][C]0.905[/C][/ROW]
[ROW][C] [/C][C]76[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197972&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197972&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)
Group30.1870.905
76



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){
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<-levene.test(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')