FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 28 Oct 2010 20:11:30 +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/2010/Oct/28/t1288296619y98xtk1m62ar8lx.htm/, Retrieved Fri, 03 May 2024 15:53:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=89903, Retrieved Fri, 03 May 2024 15:53:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact206

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)] [Golfballs] [2010-10-25 12:27:51] [b98453cac15ba1066b407e146608df68]
F   PD  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q6.1 KT] [2010-10-28 19:53:10] [afe9379cca749d06b3d6872e02cc47ed]
F    D      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws5 Q6.2 LT] [2010-10-28 20:11:30] [aa6b599ccd367bc74fed0d8f67004a46] [Current]
F             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Taak 6: lange ter...] [2010-10-29 18:12:48] [74deae64b71f9d77c839af86f7c687b5]
F R P         [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS 5 Q 6] [2010-11-02 16:59:42] [4f85667043e8913570b3eb8f368f82b2]
-             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-03 06:51:59] [b64b273f7a25c5bb07ff2f026b8ce952]
-               [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2010-11-03 06:54:41] [b64b273f7a25c5bb07ff2f026b8ce952]
- R           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws 5 - opdracht 6] [2011-11-04 15:04:06] [4b648d52023f19d55c572f0eddd72b1f]
- R PD        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 taak 6] [2012-10-29 16:52:49] [ebc10d82be597731a57172229e4f44b7]
- R P         [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Q6 - lange termijn] [2012-10-29 20:59:13] [74be16979710d4c4e7c6647856088456]
- R             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2012-10-30 18:16:35] [74be16979710d4c4e7c6647856088456]
- R           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS 5 vraag 6 ] [2013-11-03 14:44:57] [16ce55620e4b91ec00a4b56aea2a2582]
Feedback Forum
2010-11-08 20:57:38 [411b43619fc9db329bbcdbf7261c55fb] [reply] 
Bij de analyse op lange termijn heeft de auteur de juiste berekening gebruikt. Hij geeft wel een verkeerde conclusie. Er is namelijk geen verschil merkbaar op lange termijn (bij de 3 vergelijkingen van de treatments is er telkens een hoge p-waarde = dus een hoge kans op vergissen bij het verwerpen van de nulhypothese). De rede hiervoor is dat er geen rekening wordt gehouden met de inspanning van de student. Men zegt dus niks over de efficiëntie van het leren.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1	'T'
-1	'T'
1	'T'
0	'T'
0	'T'
0	'T'
0	'T'
1	'T'
1	'T'
-1	'T'
0	'T'
1	'T'
1	'T'
0	'T'
0	'T'
-1	'T'
0	'T'
1	'T'
1	'T'
0	'T'
-1	'T'
0	'T'
0	'T'
0	'T'
0	'T'
-1	'T'
-1	'T'
1	'T'
1	'T'
-1	'T'
1	'E'
1	'E'
0	'E'
0	'E'
0	'E'
-1	'E'
0	'E'
1	'E'
1	'E'
0	'E'
-1	'E'
0	'E'
0	'E'
1	'E'
0	'E'
1	'E'
0	'E'
1	'E'
1	'E'
0	'E'
1	'E'
0	'E'
0	'E'
0	'E'
1	'E'
0	'E'
1	'E'
0	'E'
0	'E'
0	'E'
0	'S'
0	'S'
0	'S'
0	'S'
0	'S'
0	'S'
1	'S'
0	'S'
0	'S'
0	'S'
1	'S'
1	'S'
1	'S'
0	'S'
1	'S'
0	'S'
1	'S'
-1	'S'
0	'S'
1	'S'
0	'S'
0	'S'
0	'S'
0	'S'
0	'S'
-1	'S'
1	'S'
0	'S'
1	'S'
0	'S'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89903&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89903&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89903&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






ANOVA Model
Answer ~ Treatment
means0.3-0.067-0.267

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Answer  ~  Treatment \tabularnewline
means & 0.3 & -0.067 & -0.267 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89903&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Answer  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]0.3[/C][C]-0.067[/C][C]-0.267[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89903&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89903&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
Answer ~ Treatment
means0.3-0.067-0.267






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment21.1560.5781.3720.259
Residuals8736.6330.421 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 2 & 1.156 & 0.578 & 1.372 & 0.259 \tabularnewline
Residuals & 87 & 36.633 & 0.421 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89903&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]2[/C][C]1.156[/C][C]0.578[/C][C]1.372[/C][C]0.259[/C][/ROW]
[ROW][C]Residuals[/C][C]87[/C][C]36.633[/C][C]0.421[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89903&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89903&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)
Treatment21.1560.5781.3720.259
Residuals8736.6330.421






Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-E-0.067-0.4660.3330.917
T-E-0.267-0.6660.1330.255
T-S-0.2-0.60.20.46

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-E & -0.067 & -0.466 & 0.333 & 0.917 \tabularnewline
T-E & -0.267 & -0.666 & 0.133 & 0.255 \tabularnewline
T-S & -0.2 & -0.6 & 0.2 & 0.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89903&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]S-E[/C][C]-0.067[/C][C]-0.466[/C][C]0.333[/C][C]0.917[/C][/ROW]
[ROW][C]T-E[/C][C]-0.267[/C][C]-0.666[/C][C]0.133[/C][C]0.255[/C][/ROW]
[ROW][C]T-S[/C][C]-0.2[/C][C]-0.6[/C][C]0.2[/C][C]0.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89903&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89903&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
S-E-0.067-0.4660.3330.917
T-E-0.267-0.6660.1330.255
T-S-0.2-0.60.20.46






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group21.2470.292
87 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.247 & 0.292 \tabularnewline
  & 87 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89903&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]1.247[/C][C]0.292[/C][/ROW]
[ROW][C] [/C][C]87[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89903&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89903&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)
Group21.2470.292
87


Figures (Output of Computation)

Input Parameters & R Code

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')