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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software ModuleIan.Hollidayrwasp_One Factor ANOVA.wasp
Title produced by softwareChi Square Measure of Association- Free Statistics Software (Calculator)
Date of computationThu, 03 Dec 2009 17:08:11 +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/2009/Dec/03/t12598565276ud831fwaiaokw6.htm/, Retrieved Fri, 19 Apr 2024 23:59:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62869, Retrieved Fri, 19 Apr 2024 23:59:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

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]
-   PD        [Chi Square Measure of Association- Free Statistics Software (Calculator)] [Week 9] [2009-12-03 16:08:11] [3428214290cd68816e8fabc3f06cbf95] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	88	1
56	94	3
48	90	3
32	73	3
44	68	1
39	80	2
34	86	3
41	86	3
50	91	2
39	79	1
62	96	1
52	92	3
37	72	3
50	96	3
41	70	1
55	86	3
41	87	3
56	88	3
39	79	2
52	90	2
46	95	1
44	85	1
41	90	3
50	115	1
50	84	1
44	79	3
52	94	1
54	97	2
44	86	3
52	111	2
37	87	2
52	98	3
50	87	1
36	68	3
50	88	3
52	82	1
55	111	2
31	75	1
36	94	1
49	95	2
42	80	1
37	95	1
41	68	3
30	94	2
52	88	2
30	84	1
44	101	1
66	98	1
48	78	2
43	109	3
57	102	3
46	81	3
54	97	3
48	75	2
48	97	2
62	101	3
58	101	3
58	95	2
62	95	2
46	95	3
34	90	2
66	107	3
52	92	3
55	86	2
55	70	2
57	95	3
56	96	3
55	91	2
56	87	1
54	92	2
55	97	2
46	102	2
52	91	2
32	68	3
44	88	2
46	97	3
59	90	1
46	101	3
46	94	3
54	101	1
66	109	1
56	100	2
59	103	1
57	94	3
52	97	1
48	85	3
44	75	2
41	77	3
50	87	1
48	78	1
48	108	2
59	97	3
34	105	1
46	106	3
54	107	1
55	95	2
54	107	2
59	115	3
44	101	3
54	85	1
52	90	3
66	115	3
44	95	3
57	97	2
39	112	3
60	97	3
45	77	3
41	90	3
50	94	1
39	103	3
43	77	1
48	98	3
37	90	3
58	111	3
46	77	2
43	88	3
44	75	2
34	92	3
30	78	2
50	106	2
39	80	2
37	87	3
55	92	3
41	111	1
39	86	3
36	85	3
43	90	2
50	101	1
55	94	3
43	86	3
60	86	3
48	90	2
30	75	1
43	86	3
39	91	3
52	97	3
39	91	2
39	70	3
56	98	2
59	96	3
46	95	3
57	100	2
50	95	3
54	97	3
50	97	3
60	92	3
59	115	1
41	88	3
48	87	2
59	100	3
60	98	3
56	102	1
51	96	3

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' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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' @ 72.249.127.135 \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62869&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' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62869&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' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






ANOVA Model
MC30VRB ~ MOMAGE
means47.7570.7430.419

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MOMAGE
 \tabularnewline
means & 47.757 & 0.743 & 0.419 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62869&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MOMAGE
[/C][/ROW]
[ROW][C]means[/C][C]47.757[/C][C]0.743[/C][C]0.419[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62869&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 ~ MOMAGE
means47.7570.7430.419






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MOMAGE 210.8885.4440.0730.929
Residuals15011132.02774.214 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MOMAGE
 & 2 & 10.888 & 5.444 & 0.073 & 0.929 \tabularnewline
Residuals & 150 & 11132.027 & 74.214 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62869&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]MOMAGE
[/C][C]2[/C][C]10.888[/C][C]5.444[/C][C]0.073[/C][C]0.929[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]11132.027[/C][C]74.214[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62869&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62869&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)
MOMAGE 210.8885.4440.0730.929
Residuals15011132.02774.214






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10.743-3.8555.3410.923
3-10.419-3.6874.5250.968
3-2-0.324-4.2643.6150.979

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 0.743 & -3.855 & 5.341 & 0.923 \tabularnewline
3-1 & 0.419 & -3.687 & 4.525 & 0.968 \tabularnewline
3-2 & -0.324 & -4.264 & 3.615 & 0.979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62869&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]2-1[/C][C]0.743[/C][C]-3.855[/C][C]5.341[/C][C]0.923[/C][/ROW]
[ROW][C]3-1[/C][C]0.419[/C][C]-3.687[/C][C]4.525[/C][C]0.968[/C][/ROW]
[ROW][C]3-2[/C][C]-0.324[/C][C]-4.264[/C][C]3.615[/C][C]0.979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62869&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62869&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
2-10.743-3.8555.3410.923
3-10.419-3.6874.5250.968
3-2-0.324-4.2643.6150.979






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group21.2150.3
150 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.215 & 0.3 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62869&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]1.215[/C][C]0.3[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62869&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62869&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)
Group21.2150.3
150


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 3 ; par3 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 3 ; 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()
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')