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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, 29 Nov 2011 08:44:51 -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/29/t13225744411nl2e4vj7nzdwqt.htm/, Retrieved Thu, 25 Apr 2024 15:19:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148352, Retrieved Thu, 25 Apr 2024 15:19:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

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]
- R PD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [MC30VRB x MVRIQ wk8] [2011-11-29 13:39:09] [8111443edfba9411dec7535134ec4584]
-   P               [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [schlyear7 x mvriq] [2011-11-29 13:44:51] [3b814a39bd96aca377cd640ac3a5a4ff] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'AstonUniversity' @ aston.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 & 12 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148352&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148352&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148352&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 time12 seconds
R Server'AstonUniversity' @ aston.wessa.net






ANOVA Model
WISCRY7V ~ MVRBIQ0
means90.2732.74-1.273

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MVRBIQ0 \tabularnewline
means & 90.273 & 2.74 & -1.273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148352&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]90.273[/C][C]2.74[/C][C]-1.273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148352&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148352&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
WISCRY7V ~ MVRBIQ0
means90.2732.74-1.273






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ02421.901210.9511.8790.156
Residuals14816617.715112.282 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 2 & 421.901 & 210.951 & 1.879 & 0.156 \tabularnewline
Residuals & 148 & 16617.715 & 112.282 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148352&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]421.901[/C][C]210.951[/C][C]1.879[/C][C]0.156[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]16617.715[/C][C]112.282[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148352&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148352&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)
MVRBIQ02421.901210.9511.8790.156
Residuals14816617.715112.282






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-12.74-1.9797.4590.357
3-1-1.273-7.3374.7920.873
3-2-4.013-9.531.5050.2

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 2.74 & -1.979 & 7.459 & 0.357 \tabularnewline
3-1 & -1.273 & -7.337 & 4.792 & 0.873 \tabularnewline
3-2 & -4.013 & -9.53 & 1.505 & 0.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148352&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]2.74[/C][C]-1.979[/C][C]7.459[/C][C]0.357[/C][/ROW]
[ROW][C]3-1[/C][C]-1.273[/C][C]-7.337[/C][C]4.792[/C][C]0.873[/C][/ROW]
[ROW][C]3-2[/C][C]-4.013[/C][C]-9.53[/C][C]1.505[/C][C]0.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148352&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148352&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
2-12.74-1.9797.4590.357
3-1-1.273-7.3374.7920.873
3-2-4.013-9.531.5050.2






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.8550.427
148 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.855 & 0.427 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148352&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]0.855[/C][C]0.427[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148352&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148352&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)
Group20.8550.427
148


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 3 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; 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')