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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 computationThu, 07 Nov 2013 08:42:40 -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/2013/Nov/07/t1383831786nc9kcfnxxj8b68s.htm/, Retrieved Thu, 02 May 2024 20:20:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223303, Retrieved Thu, 02 May 2024 20:20:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115

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             [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] [1fbabd0bc3ea20d1a9860b46395f5a6a] [Current]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers IQ and IQ...] [2013-11-07 13:46:47] [77b1ee5de7e10572d5aa90ce039d7689]
-    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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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	"Low"
56	"Low"
48	"Low"
32	"Low"
44	"Low"
39	"Low"
34	"Low"
41	"Low"
50	"Low"
39	"Low"
62	"Low"
52	"Low"
37	"Low"
50	"Low"
41	"Low"
55	"Low"
41	"Low"
56	"Low"
39	"Low"
52	"Low"
46	"Low"
44	"Low"
41	"Low"
50	"Low"
50	"Low"
44	"Low"
52	"Low"
54	"Low"
44	"Low"
52	"Low"
37	"Low"
52	"Low"
50	"Low"
36	"Low"
50	"Low"
52	"Low"
55	"Low"
31	"Low"
36	"Low"
49	"Low"
42	"Low"
37	"Low"
41	"Low"
30	"Low"
52	"Low"
30	"Low"
44	"Low"
66	"Low"
48	"Low"
43	"Low"
57	"Low"
46	"Low"
54	"Medium"
48	"Medium"
48	"Medium"
62	"Medium"
58	"Medium"
58	"Medium"
62	"Medium"
46	"Medium"
34	"Medium"
66	"Medium"
52	"Medium"
55	"Medium"
55	"Medium"
57	"Medium"
56	"Medium"
55	"Medium"
56	"Medium"
54	"Medium"
55	"Medium"
46	"Medium"
52	"Medium"
32	"Medium"
44	"Medium"
46	"Medium"
59	"Medium"
46	"Medium"
46	"Medium"
54	"Medium"
66	"Medium"
56	"Medium"
59	"Medium"
57	"Medium"
52	"Medium"
48	"Medium"
44	"Medium"
41	"Medium"
50	"Medium"
48	"Medium"
48	"Medium"
59	"Medium"
34	"Medium"
46	"Medium"
54	"Medium"
55	"Medium"
54	"Medium"
59	"Medium"
44	"Medium"
54	"Medium"
52	"Medium"
66	"Medium"
44	"Medium"
57	"Medium"
39	"Medium"
60	"Medium"
45	"Medium"
41	"Medium"
50	"Medium"
39	"Medium"
43	"Medium"
48	"Medium"
37	"Medium"
58	"Medium"
46	"Medium"
43	"Medium"
44	"Medium"
34	"Medium"
30	"Medium"
50	"Medium"
39	"Medium"
37	"Medium"
55	"Medium"
41	"Medium"
39	"Medium"
36	"Medium"
43	"Medium"
50	"Medium"
55	"Medium"
43	"High"
60	"High"
48	"High"
30	"High"
43	"High"
39	"High"
52	"High"
39	"High"
39	"High"
56	"High"
59	"High"
46	"High"
57	"High"
50	"High"
54	"High"
50	"High"
60	"High"
59	"High"
41	"High"
48	"High"
59	"High"
60	"High"
56	"High"
51	"High"

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'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223303&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223303&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223303&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'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
MC30VRB ~ MVRBIQ0
means49.958-4.478-0.543

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MVRBIQ0 \tabularnewline
means & 49.958 & -4.478 & -0.543 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223303&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]49.958[/C][C]-4.478[/C][C]-0.543[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223303&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223303&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
means49.958-4.478-0.543






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ02572.275286.1374.060.019
Residuals15010570.6470.471 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 2 & 572.275 & 286.137 & 4.06 & 0.019 \tabularnewline
Residuals & 150 & 10570.64 & 70.471 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223303&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]572.275[/C][C]286.137[/C][C]4.06[/C][C]0.019[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]10570.64[/C][C]70.471[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223303&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223303&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)
MVRBIQ02572.275286.1374.060.019
Residuals15010570.6470.471






Tukey Honest Significant Difference Comparisons
difflwruprp adj
Low-High-4.478-9.3810.4260.081
Medium-High-0.543-5.1884.1030.959
Medium-Low3.9350.3687.5020.027

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
Low-High & -4.478 & -9.381 & 0.426 & 0.081 \tabularnewline
Medium-High & -0.543 & -5.188 & 4.103 & 0.959 \tabularnewline
Medium-Low & 3.935 & 0.368 & 7.502 & 0.027 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223303&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]-4.478[/C][C]-9.381[/C][C]0.426[/C][C]0.081[/C][/ROW]
[ROW][C]Medium-High[/C][C]-0.543[/C][C]-5.188[/C][C]4.103[/C][C]0.959[/C][/ROW]
[ROW][C]Medium-Low[/C][C]3.935[/C][C]0.368[/C][C]7.502[/C][C]0.027[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223303&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223303&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
Low-High-4.478-9.3810.4260.081
Medium-High-0.543-5.1884.1030.959
Medium-Low3.9350.3687.5020.027






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.0110.989
150 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.011 & 0.989 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223303&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]0.011[/C][C]0.989[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223303&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223303&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)
Group20.0110.989
150


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')