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 computationSat, 26 Nov 2011 10:56:30 -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/2011/Nov/26/t1322323023r4mlz0dbgw0ilp2.htm/, Retrieved Mon, 30 Jan 2023 00:56:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147423, Retrieved Mon, 30 Jan 2023 00:56:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
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]
- R PD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mothers IQ and ch...] [2011-11-26 15:56:30] [23a0554fd40bcbfca1fa96ec3cebf579] [Current]
-   P               [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mothers IQ and ch...] [2011-11-26 16:11:40] [c2d7eae68f5ec0337d2d2ba826377ba0]
Feedback Forum

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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \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=147423&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]'Gertrude Mary Cox' @ cox.wessa.net[/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=147423&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147423&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
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 ~ MVRBIQ0
means46.9780.95.5

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MVRBIQ0
 \tabularnewline
means & 46.978 & 0.9 & 5.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147423&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MVRBIQ0
[/C][/ROW]
[ROW][C]means[/C][C]46.978[/C][C]0.9[/C][C]5.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147423&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147423&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
MC30VRB ~ MVRBIQ0
means46.9780.95.5







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ0 2496.489248.2443.5360.032
Residuals14810391.49870.213

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0
 & 2 & 496.489 & 248.244 & 3.536 & 0.032 \tabularnewline
Residuals & 148 & 10391.498 & 70.213 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147423&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]2[/C][C]496.489[/C][C]248.244[/C][C]3.536[/C][C]0.032[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]10391.498[/C][C]70.213[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147423&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147423&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)
MVRBIQ0 2496.489248.2443.5360.032
Residuals14810391.49870.213







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10.9-2.7554.5540.829
3-15.50.43410.5660.03
3-24.6-0.0819.2810.055

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 0.9 & -2.755 & 4.554 & 0.829 \tabularnewline
3-1 & 5.5 & 0.434 & 10.566 & 0.03 \tabularnewline
3-2 & 4.6 & -0.081 & 9.281 & 0.055 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147423&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]0.9[/C][C]-2.755[/C][C]4.554[/C][C]0.829[/C][/ROW]
[ROW][C]3-1[/C][C]5.5[/C][C]0.434[/C][C]10.566[/C][C]0.03[/C][/ROW]
[ROW][C]3-2[/C][C]4.6[/C][C]-0.081[/C][C]9.281[/C][C]0.055[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147423&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147423&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
2-10.9-2.7554.5540.829
3-15.50.43410.5660.03
3-24.6-0.0819.2810.055







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.0140.987
148

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.014 & 0.987 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147423&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]0.014[/C][C]0.987[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147423&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147423&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)
Group20.0140.987
148



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()
}
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')