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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 computationTue, 18 Nov 2014 15:29:57 +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/Nov/18/t1416324613oqpibzm1nwuw2xb.htm/, Retrieved Sun, 19 May 2024 20:35:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=256160, Retrieved Sun, 19 May 2024 20:35:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RM D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-11-18 15:29:57] [b1f927f029ae9c10d0e4101a3d680096] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	 2.00 
56	 2.00 
48	 3.00 
32	 1.00 
44	 1.00 
39	 2.00 
34	 2.00 
41	 1.00 
50	 3.00 
39	 1.00 
62	 3.00 
52	 2.00 
37	 1.00 
50	 2.00 
41	 2.00 
55	 2.00 
41	 1.00 
56	 3.00 
39	 2.00 
52	 1.00 
46	 1.00 
44	 1.00 
41	 2.00 
50	 3.00 
50	 2.00 
44	 2.00 
52	 2.00 
54	 2.00 
44	 2.00 
52	 3.00 
37	 2.00 
52	 2.00 
50	 2.00 
36	 1.00 
50	 2.00 
52	 2.00 
55	 3.00 
31	 1.00 
36	 2.00 
49	 1.00 
42	 2.00 
37	 2.00 
41	 2.00 
30	 2.00 
52	 2.00 
30	 1.00 
44	 2.00 
66	 2.00 
48	 1.00 
43	 3.00 
57	 1.00 
46	 1.00 
54	 1.00 
48	 2.00 
48	 2.00 
62	 1.00 
58	 1.00 
58	 2.00 
62	 2.00 
46	 2.00 
34	 2.00 
66	 111.00 
52	 2.00 
55	 1.00 
55	 1.00 
57	 2.00 
56	 2.00 
55	 2.00 
56	 97.00 
54	 2.00 
55	 2.00 
46	 99.00 
52	 1.00 
32	 2.00 
44	 1.00 
46	 2.00 
59	 2.00 
46	 2.00 
46	 2.00 
54	 3.00 
66	 3.00 
56	 2.00 
59	 2.00 
57	 2.00 
52	 2.00 
48	 2.00 
44	 2.00 
41	 1.00 
50	 1.00 
48	 1.00 
48	 3.00 
59	 2.00 
34	 2.00 
46	 2.00 
54	 2.00 
55	 1.00 
54	 2.00 
59	 2.00 
44	 2.00 
54	 1.00 
52	 2.00 
66	 3.00 
44	 2.00 
57	 1.00 
39	 1.00 
60	 1.00 
45	 1.00 
41	 2.00 
50	 2.00 
39	 3.00 
43	 2.00 
48	 2.00 
37	 2.00 
58	 3.00 
46	 1.00 
43	 3.00 
44	 1.00 
34	 2.00 
30	 2.00 
50	 2.00 
39	 1.00 
37	 2.00 
55	 1.00 
41	 3.00 
39	 2.00 
36	 2.00 
43	 1.00 
50	 3.00 
55	 2.00 
43	 1.00 
60	 1.00 
48	 1.00 
30	 1.00 
43	 2.00 
39	 3.00 
52	 2.00 
39	 2.00 
39	 1.00 
56	 2.00 
59	 1.00 
46	 1.00 
57	 2.00 
50	 2.00 
54	 2.00 
50	 2.00 
60	 3.00 
59	 3.00 
41	 3.00 
48	 2.00 
59	 2.00 
60	 2.00 
56	 1.00 
51	 1.00

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256160&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256160&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256160&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






ANOVA Model
MC30VRB ~ MVRBIQ0
means46.97819.0220.7334.459.022-0.978

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MVRBIQ0 \tabularnewline
means & 46.978 & 19.022 & 0.733 & 4.45 & 9.022 & -0.978 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256160&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]46.978[/C][C]19.022[/C][C]0.733[/C][C]4.45[/C][C]9.022[/C][C]-0.978[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256160&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256160&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
MC30VRB ~ MVRBIQ0
means46.97819.0220.7334.459.022-0.978






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ05689.734137.9471.940.091
Residuals14710453.18171.11 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 5 & 689.734 & 137.947 & 1.94 & 0.091 \tabularnewline
Residuals & 147 & 10453.181 & 71.11 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256160&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]MVRBIQ0[/C][C]5[/C][C]689.734[/C][C]137.947[/C][C]1.94[/C][C]0.091[/C][/ROW]
[ROW][C]Residuals[/C][C]147[/C][C]10453.181[/C][C]71.11[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256160&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256160&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)
MVRBIQ05689.734137.9471.940.091
Residuals14710453.18171.11






Tukey Honest Significant Difference Comparisons
difflwruprp adj
111-119.022-5.59243.6360.23
2-10.733-3.7435.2090.997
3-14.45-1.96310.8630.345
97-19.022-15.59233.6360.897
99-1-0.978-25.59223.6361
2-111-18.289-42.7866.2080.265
3-111-14.571-39.49510.3520.542
97-111-10-44.43724.4370.96
99-111-20-54.43714.4370.549
3-23.718-2.239.6660.466
97-28.289-16.20832.7860.925
99-2-1.711-26.20822.7861
97-34.571-20.35229.4950.995
99-3-5.429-30.35219.4950.989
99-97-10-44.43724.4370.96

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
111-1 & 19.022 & -5.592 & 43.636 & 0.23 \tabularnewline
2-1 & 0.733 & -3.743 & 5.209 & 0.997 \tabularnewline
3-1 & 4.45 & -1.963 & 10.863 & 0.345 \tabularnewline
97-1 & 9.022 & -15.592 & 33.636 & 0.897 \tabularnewline
99-1 & -0.978 & -25.592 & 23.636 & 1 \tabularnewline
2-111 & -18.289 & -42.786 & 6.208 & 0.265 \tabularnewline
3-111 & -14.571 & -39.495 & 10.352 & 0.542 \tabularnewline
97-111 & -10 & -44.437 & 24.437 & 0.96 \tabularnewline
99-111 & -20 & -54.437 & 14.437 & 0.549 \tabularnewline
3-2 & 3.718 & -2.23 & 9.666 & 0.466 \tabularnewline
97-2 & 8.289 & -16.208 & 32.786 & 0.925 \tabularnewline
99-2 & -1.711 & -26.208 & 22.786 & 1 \tabularnewline
97-3 & 4.571 & -20.352 & 29.495 & 0.995 \tabularnewline
99-3 & -5.429 & -30.352 & 19.495 & 0.989 \tabularnewline
99-97 & -10 & -44.437 & 24.437 & 0.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256160&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]111-1[/C][C]19.022[/C][C]-5.592[/C][C]43.636[/C][C]0.23[/C][/ROW]
[ROW][C]2-1[/C][C]0.733[/C][C]-3.743[/C][C]5.209[/C][C]0.997[/C][/ROW]
[ROW][C]3-1[/C][C]4.45[/C][C]-1.963[/C][C]10.863[/C][C]0.345[/C][/ROW]
[ROW][C]97-1[/C][C]9.022[/C][C]-15.592[/C][C]33.636[/C][C]0.897[/C][/ROW]
[ROW][C]99-1[/C][C]-0.978[/C][C]-25.592[/C][C]23.636[/C][C]1[/C][/ROW]
[ROW][C]2-111[/C][C]-18.289[/C][C]-42.786[/C][C]6.208[/C][C]0.265[/C][/ROW]
[ROW][C]3-111[/C][C]-14.571[/C][C]-39.495[/C][C]10.352[/C][C]0.542[/C][/ROW]
[ROW][C]97-111[/C][C]-10[/C][C]-44.437[/C][C]24.437[/C][C]0.96[/C][/ROW]
[ROW][C]99-111[/C][C]-20[/C][C]-54.437[/C][C]14.437[/C][C]0.549[/C][/ROW]
[ROW][C]3-2[/C][C]3.718[/C][C]-2.23[/C][C]9.666[/C][C]0.466[/C][/ROW]
[ROW][C]97-2[/C][C]8.289[/C][C]-16.208[/C][C]32.786[/C][C]0.925[/C][/ROW]
[ROW][C]99-2[/C][C]-1.711[/C][C]-26.208[/C][C]22.786[/C][C]1[/C][/ROW]
[ROW][C]97-3[/C][C]4.571[/C][C]-20.352[/C][C]29.495[/C][C]0.995[/C][/ROW]
[ROW][C]99-3[/C][C]-5.429[/C][C]-30.352[/C][C]19.495[/C][C]0.989[/C][/ROW]
[ROW][C]99-97[/C][C]-10[/C][C]-44.437[/C][C]24.437[/C][C]0.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256160&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256160&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
111-119.022-5.59243.6360.23
2-10.733-3.7435.2090.997
3-14.45-1.96310.8630.345
97-19.022-15.59233.6360.897
99-1-0.978-25.59223.6361
2-111-18.289-42.7866.2080.265
3-111-14.571-39.49510.3520.542
97-111-10-44.43724.4370.96
99-111-20-54.43714.4370.549
3-23.718-2.239.6660.466
97-28.289-16.20832.7860.925
99-2-1.711-26.20822.7861
97-34.571-20.35229.4950.995
99-3-5.429-30.35219.4950.989
99-97-10-44.43724.4370.96






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group51.1360.344
147 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.136 & 0.344 \tabularnewline
  & 147 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256160&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]5[/C][C]1.136[/C][C]0.344[/C][/ROW]
[ROW][C] [/C][C]147[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256160&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256160&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)
Group51.1360.344
147


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')