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, 27 Oct 2011 14:58:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/27/t1319742100sdhmqki8nen07p9.htm/, Retrieved Thu, 16 May 2024 18:13:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=137487, Retrieved Thu, 16 May 2024 18:13:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact44

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)] [] [2011-10-27 18:58:15] [694c30abd2a3b2ee5cb46fc74cb5bfb9] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	3	-1	1
0	-1	-1	1
1	4	1	1.5
0	0	0	0
0	-1	0	0
0	-1	0	1
0	-1	0	1
1	0	1	1
1	4	1	2
0	0	-1	1
0	4	0	2
1	0	1	0
1	2	1	0
1	0	0	2
0	0	NA	NA
0	-1	0	1
0	0	-1	1
0	-1	0	-0.5
1	0	1	2
0	2	1	0
0	1	0	1
0	0	-1	-1
0	2	NA	NA
-1	-1	NA	NA
0	2	0	1
-1	-1	0	-1
0	-1	NA	NA
0	0	NA	NA
0	1	0	2
0	-1	0	0
-1	-1	-1	-0.5
0	3	-1	1
0	0	1	0.5
0	1	NA	NA
0	0	1	0.5
0	-1	NA	NA
0	3	-1	1

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'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=137487&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=137487&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137487&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'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
post2-pre ~ post4-pre
means-10.51.33311.66752.81

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
post2-pre  ~  post4-pre \tabularnewline
means & -1 & 0.5 & 1.333 & 1 & 1.667 & 5 & 2.8 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137487&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]post2-pre  ~  post4-pre[/C][/ROW]
[ROW][C]means[/C][C]-1[/C][C]0.5[/C][C]1.333[/C][C]1[/C][C]1.667[/C][C]5[/C][C]2.8[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137487&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137487&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
post2-pre ~ post4-pre
means-10.51.33311.66752.81






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
post4-pre729.8894.271.8960.107
Residuals2965.32.252 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
post4-pre & 7 & 29.889 & 4.27 & 1.896 & 0.107 \tabularnewline
Residuals & 29 & 65.3 & 2.252 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137487&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]post4-pre[/C][C]7[/C][C]29.889[/C][C]4.27[/C][C]1.896[/C][C]0.107[/C][/ROW]
[ROW][C]Residuals[/C][C]29[/C][C]65.3[/C][C]2.252[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137487&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137487&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)
post4-pre729.8894.271.8960.107
Residuals2965.32.252






Tukey Honest Significant Difference Comparisons
difflwruprp adj
-1--0.50.5-4.3945.3941
0--0.51.333-2.6635.330.954
0.5--0.51-3.8945.8940.997
1--0.51.667-2.0715.4050.824
1.5--0.55-0.99410.9940.157
2--0.52.8-1.2956.8950.364
NA--0.51-2.9244.9240.99
0--10.833-3.1634.830.997
0.5--10.5-4.3945.3941
1--11.167-2.5714.9050.968
1.5--14.5-1.49410.4940.257
2--12.3-1.7956.3950.605
NA--10.5-3.4244.4241
0.5-0-0.333-4.333.6631
1-00.333-2.1142.7811
1.5-03.667-1.628.9530.347
2-01.467-1.4974.430.738
NA-0-0.333-3.0562.391
1-0.50.667-3.0714.4050.999
1.5-0.54-1.9949.9940.394
2-0.51.8-2.2955.8950.834
NA-0.50-3.9243.9241
1.5-13.333-1.7618.4280.418
2-11.133-1.4723.7390.841
NA-1-0.667-2.9941.6610.98
2-1.5-2.2-7.5623.1620.876
NA-1.5-4-9.2321.2320.238
NA-2-1.8-4.6661.0660.469

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
-1--0.5 & 0.5 & -4.394 & 5.394 & 1 \tabularnewline
0--0.5 & 1.333 & -2.663 & 5.33 & 0.954 \tabularnewline
0.5--0.5 & 1 & -3.894 & 5.894 & 0.997 \tabularnewline
1--0.5 & 1.667 & -2.071 & 5.405 & 0.824 \tabularnewline
1.5--0.5 & 5 & -0.994 & 10.994 & 0.157 \tabularnewline
2--0.5 & 2.8 & -1.295 & 6.895 & 0.364 \tabularnewline
NA--0.5 & 1 & -2.924 & 4.924 & 0.99 \tabularnewline
0--1 & 0.833 & -3.163 & 4.83 & 0.997 \tabularnewline
0.5--1 & 0.5 & -4.394 & 5.394 & 1 \tabularnewline
1--1 & 1.167 & -2.571 & 4.905 & 0.968 \tabularnewline
1.5--1 & 4.5 & -1.494 & 10.494 & 0.257 \tabularnewline
2--1 & 2.3 & -1.795 & 6.395 & 0.605 \tabularnewline
NA--1 & 0.5 & -3.424 & 4.424 & 1 \tabularnewline
0.5-0 & -0.333 & -4.33 & 3.663 & 1 \tabularnewline
1-0 & 0.333 & -2.114 & 2.781 & 1 \tabularnewline
1.5-0 & 3.667 & -1.62 & 8.953 & 0.347 \tabularnewline
2-0 & 1.467 & -1.497 & 4.43 & 0.738 \tabularnewline
NA-0 & -0.333 & -3.056 & 2.39 & 1 \tabularnewline
1-0.5 & 0.667 & -3.071 & 4.405 & 0.999 \tabularnewline
1.5-0.5 & 4 & -1.994 & 9.994 & 0.394 \tabularnewline
2-0.5 & 1.8 & -2.295 & 5.895 & 0.834 \tabularnewline
NA-0.5 & 0 & -3.924 & 3.924 & 1 \tabularnewline
1.5-1 & 3.333 & -1.761 & 8.428 & 0.418 \tabularnewline
2-1 & 1.133 & -1.472 & 3.739 & 0.841 \tabularnewline
NA-1 & -0.667 & -2.994 & 1.661 & 0.98 \tabularnewline
2-1.5 & -2.2 & -7.562 & 3.162 & 0.876 \tabularnewline
NA-1.5 & -4 & -9.232 & 1.232 & 0.238 \tabularnewline
NA-2 & -1.8 & -4.666 & 1.066 & 0.469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137487&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--0.5[/C][C]0.5[/C][C]-4.394[/C][C]5.394[/C][C]1[/C][/ROW]
[ROW][C]0--0.5[/C][C]1.333[/C][C]-2.663[/C][C]5.33[/C][C]0.954[/C][/ROW]
[ROW][C]0.5--0.5[/C][C]1[/C][C]-3.894[/C][C]5.894[/C][C]0.997[/C][/ROW]
[ROW][C]1--0.5[/C][C]1.667[/C][C]-2.071[/C][C]5.405[/C][C]0.824[/C][/ROW]
[ROW][C]1.5--0.5[/C][C]5[/C][C]-0.994[/C][C]10.994[/C][C]0.157[/C][/ROW]
[ROW][C]2--0.5[/C][C]2.8[/C][C]-1.295[/C][C]6.895[/C][C]0.364[/C][/ROW]
[ROW][C]NA--0.5[/C][C]1[/C][C]-2.924[/C][C]4.924[/C][C]0.99[/C][/ROW]
[ROW][C]0--1[/C][C]0.833[/C][C]-3.163[/C][C]4.83[/C][C]0.997[/C][/ROW]
[ROW][C]0.5--1[/C][C]0.5[/C][C]-4.394[/C][C]5.394[/C][C]1[/C][/ROW]
[ROW][C]1--1[/C][C]1.167[/C][C]-2.571[/C][C]4.905[/C][C]0.968[/C][/ROW]
[ROW][C]1.5--1[/C][C]4.5[/C][C]-1.494[/C][C]10.494[/C][C]0.257[/C][/ROW]
[ROW][C]2--1[/C][C]2.3[/C][C]-1.795[/C][C]6.395[/C][C]0.605[/C][/ROW]
[ROW][C]NA--1[/C][C]0.5[/C][C]-3.424[/C][C]4.424[/C][C]1[/C][/ROW]
[ROW][C]0.5-0[/C][C]-0.333[/C][C]-4.33[/C][C]3.663[/C][C]1[/C][/ROW]
[ROW][C]1-0[/C][C]0.333[/C][C]-2.114[/C][C]2.781[/C][C]1[/C][/ROW]
[ROW][C]1.5-0[/C][C]3.667[/C][C]-1.62[/C][C]8.953[/C][C]0.347[/C][/ROW]
[ROW][C]2-0[/C][C]1.467[/C][C]-1.497[/C][C]4.43[/C][C]0.738[/C][/ROW]
[ROW][C]NA-0[/C][C]-0.333[/C][C]-3.056[/C][C]2.39[/C][C]1[/C][/ROW]
[ROW][C]1-0.5[/C][C]0.667[/C][C]-3.071[/C][C]4.405[/C][C]0.999[/C][/ROW]
[ROW][C]1.5-0.5[/C][C]4[/C][C]-1.994[/C][C]9.994[/C][C]0.394[/C][/ROW]
[ROW][C]2-0.5[/C][C]1.8[/C][C]-2.295[/C][C]5.895[/C][C]0.834[/C][/ROW]
[ROW][C]NA-0.5[/C][C]0[/C][C]-3.924[/C][C]3.924[/C][C]1[/C][/ROW]
[ROW][C]1.5-1[/C][C]3.333[/C][C]-1.761[/C][C]8.428[/C][C]0.418[/C][/ROW]
[ROW][C]2-1[/C][C]1.133[/C][C]-1.472[/C][C]3.739[/C][C]0.841[/C][/ROW]
[ROW][C]NA-1[/C][C]-0.667[/C][C]-2.994[/C][C]1.661[/C][C]0.98[/C][/ROW]
[ROW][C]2-1.5[/C][C]-2.2[/C][C]-7.562[/C][C]3.162[/C][C]0.876[/C][/ROW]
[ROW][C]NA-1.5[/C][C]-4[/C][C]-9.232[/C][C]1.232[/C][C]0.238[/C][/ROW]
[ROW][C]NA-2[/C][C]-1.8[/C][C]-4.666[/C][C]1.066[/C][C]0.469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137487&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137487&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
-1--0.50.5-4.3945.3941
0--0.51.333-2.6635.330.954
0.5--0.51-3.8945.8940.997
1--0.51.667-2.0715.4050.824
1.5--0.55-0.99410.9940.157
2--0.52.8-1.2956.8950.364
NA--0.51-2.9244.9240.99
0--10.833-3.1634.830.997
0.5--10.5-4.3945.3941
1--11.167-2.5714.9050.968
1.5--14.5-1.49410.4940.257
2--12.3-1.7956.3950.605
NA--10.5-3.4244.4241
0.5-0-0.333-4.333.6631
1-00.333-2.1142.7811
1.5-03.667-1.628.9530.347
2-01.467-1.4974.430.738
NA-0-0.333-3.0562.391
1-0.50.667-3.0714.4050.999
1.5-0.54-1.9949.9940.394
2-0.51.8-2.2955.8950.834
NA-0.50-3.9243.9241
1.5-13.333-1.7618.4280.418
2-11.133-1.4723.7390.841
NA-1-0.667-2.9941.6610.98
2-1.5-2.2-7.5623.1620.876
NA-1.5-4-9.2321.2320.238
NA-2-1.8-4.6661.0660.469






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group71.2660.301
29 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 1.266 & 0.301 \tabularnewline
  & 29 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=137487&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]1.266[/C][C]0.301[/C][/ROW]
[ROW][C] [/C][C]29[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=137487&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=137487&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)
Group71.2660.301
29


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 4 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 4 ; 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')