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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_One Factor ANOVA.wasp

Title produced by software

One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation

Thu, 07 Nov 2013 08:46:47 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/07/t1383832037tv2mupt78koxmps.htm/, Retrieved Fri, 03 May 2024 12:19:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223306, Retrieved Fri, 03 May 2024 12:19:58 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

167

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             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Age at gestation ...] [2013-11-07 12:33:54] [77b1ee5de7e10572d5aa90ce039d7689]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers IQ and IQ...] [2013-11-07 13:42:40] [77b1ee5de7e10572d5aa90ce039d7689]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers IQ and IQ...] [2013-11-07 13:46:47] [1fbabd0bc3ea20d1a9860b46395f5a6a] [Current]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Maternal warmth a...] [2013-11-07 14:34:20] [77b1ee5de7e10572d5aa90ce039d7689] 
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Maternal warmth a...] [2013-11-07 14:36:55] [77b1ee5de7e10572d5aa90ce039d7689] 
- R  D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 Q1a AB] [2014-08-14 20:38:45] [74be16979710d4c4e7c6647856088456] 
- R  D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 Q1b AB] [2014-08-14 20:42:13] [74be16979710d4c4e7c6647856088456] 
- R  D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 Q2a AB] [2014-08-14 20:45:49] [74be16979710d4c4e7c6647856088456] 
- R  D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 Q2b AB] [2014-08-14 20:48:28] [74be16979710d4c4e7c6647856088456] 
- R  D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 Q3a AB] [2014-08-14 20:51:46] [74be16979710d4c4e7c6647856088456] 
- R  D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 Q3b AB] [2014-08-14 20:55:23] [74be16979710d4c4e7c6647856088456] 

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Dataseries X:

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Histogram

Boxplots

88	"Low"
94	"Low"
90	"Low"
73	"Low"
68	"Low"
80	"Low"
86	"Low"
86	"Low"
91	"Low"
79	"Low"
96	"Low"
92	"Low"
72	"Low"
96	"Low"
70	"Low"
86	"Low"
87	"Low"
88	"Low"
79	"Low"
90	"Low"
95	"Low"
85	"Low"
90	"Low"
115	"Low"
84	"Low"
79	"Low"
94	"Low"
97	"Low"
86	"Low"
111	"Low"
87	"Low"
98	"Low"
87	"Low"
68	"Low"
88	"Low"
82	"Low"
111	"Low"
75	"Low"
94	"Low"
95	"Low"
80	"Low"
95	"Low"
68	"Low"
94	"Low"
88	"Low"
84	"Low"
101	"Low"
98	"Low"
78	"Low"
109	"Low"
102	"Low"
81	"Low"
97	"Medium"
75	"Medium"
97	"Medium"
101	"Medium"
101	"Medium"
95	"Medium"
95	"Medium"
95	"Medium"
90	"Medium"
107	"Medium"
92	"Medium"
86	"Medium"
70	"Medium"
95	"Medium"
96	"Medium"
91	"Medium"
87	"Medium"
92	"Medium"
97	"Medium"
102	"Medium"
91	"Medium"
68	"Medium"
88	"Medium"
97	"Medium"
90	"Medium"
101	"Medium"
94	"Medium"
101	"Medium"
109	"Medium"
100	"Medium"
103	"Medium"
94	"Medium"
97	"Medium"
85	"Medium"
75	"Medium"
77	"Medium"
87	"Medium"
78	"Medium"
108	"Medium"
97	"Medium"
105	"Medium"
106	"Medium"
107	"Medium"
95	"Medium"
107	"Medium"
115	"Medium"
101	"Medium"
85	"Medium"
90	"Medium"
115	"Medium"
95	"Medium"
97	"Medium"
112	"Medium"
97	"Medium"
77	"Medium"
90	"Medium"
94	"Medium"
103	"Medium"
77	"Medium"
98	"Medium"
90	"Medium"
111	"Medium"
77	"Medium"
88	"Medium"
75	"Medium"
92	"Medium"
78	"Medium"
106	"Medium"
80	"Medium"
87	"Medium"
92	"Medium"
111	"Medium"
86	"Medium"
85	"Medium"
90	"Medium"
101	"Medium"
94	"Medium"
86	"High"
86	"High"
90	"High"
75	"High"
86	"High"
91	"High"
97	"High"
91	"High"
70	"High"
98	"High"
96	"High"
95	"High"
100	"High"
95	"High"
97	"High"
97	"High"
92	"High"
115	"High"
88	"High"
87	"High"
100	"High"
98	"High"
102	"High"
96	"High"

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223306&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223306&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223306&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

ANOVA Model
WISCRY7V ~ MVRBIQ0
means	92.833	-4.564	0.803

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MVRBIQ0 \tabularnewline
means & 92.833 & -4.564 & 0.803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223306&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]92.833[/C][C]-4.564[/C][C]0.803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223306&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223306&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
WISCRY7V ~ MVRBIQ0
means	92.833	-4.564	0.803

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
MVRBIQ0	2	931.559	465.779	4.192	0.017
Residuals	150	16665.382	111.103

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 2 & 931.559 & 465.779 & 4.192 & 0.017 \tabularnewline
Residuals & 150 & 16665.382 & 111.103 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223306&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]931.559[/C][C]465.779[/C][C]4.192[/C][C]0.017[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]16665.382[/C][C]111.103[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223306&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223306&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
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
MVRBIQ0	2	931.559	465.779	4.192	0.017
Residuals	150	16665.382	111.103

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
Low-High	-4.564	-10.722	1.593	0.189
Medium-High	0.803	-5.03	6.636	0.943
Medium-Low	5.367	0.888	9.846	0.014

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
Low-High & -4.564 & -10.722 & 1.593 & 0.189 \tabularnewline
Medium-High & 0.803 & -5.03 & 6.636 & 0.943 \tabularnewline
Medium-Low & 5.367 & 0.888 & 9.846 & 0.014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223306&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]Low-High[/C][C]-4.564[/C][C]-10.722[/C][C]1.593[/C][C]0.189[/C][/ROW]
[ROW][C]Medium-High[/C][C]0.803[/C][C]-5.03[/C][C]6.636[/C][C]0.943[/C][/ROW]
[ROW][C]Medium-Low[/C][C]5.367[/C][C]0.888[/C][C]9.846[/C][C]0.014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223306&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223306&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
	diff	lwr	upr	p adj
Low-High	-4.564	-10.722	1.593	0.189
Medium-High	0.803	-5.03	6.636	0.943
Medium-Low	5.367	0.888	9.846	0.014

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	2	0.799	0.452
	150

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.799 & 0.452 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223306&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]0.799[/C][C]0.452[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223306&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223306&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
	Df	F value	Pr(>F)
Group	2	0.799	0.452
	150

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code