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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 computationSun, 04 Nov 2012 17:56:03 -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/2012/Nov/04/t1352069787267gj3js6yxyfq2.htm/, Retrieved Mon, 29 Apr 2024 01:31:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185949, Retrieved Mon, 29 Apr 2024 01:31:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

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)] [Mothers age and 3...] [2012-11-01 12:34:44] [74be16979710d4c4e7c6647856088456]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mothers IQ & 30mo...] [2012-11-04 22:40:46] [06f6c2edf62285b5081418857590532e]
-                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mothers IQ & 30mo...] [2012-11-04 22:48:01] [06f6c2edf62285b5081418857590532e]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [maternal warmth &...] [2012-11-04 22:56:03] [b70eeae1247aa3d4059588e0dcf1d5ee] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	1
36	1
56	1
48	1
32	1
44	1
39	1
34	1
41	1
50	1
39	1
62	1
52	1
37	1
50	1
41	1
55	1
41	1
56	1
39	1
52	1
46	1
44	1
48	1
41	1
50	1
50	1
44	1
52	1
54	1
44	1
52	1
37	1
52	1
50	1
36	1
50	1
52	1
55	1
31	1
36	1
49	1
42	2
37	2
41	2
30	2
52	2
30	2
41	2
44	2
66	2
48	2
43	2
57	2
46	2
54	2
48	2
48	2
52	2
62	2
58	2
58	2
62	2
48	2
46	2
34	2
66	2
52	2
55	2
55	2
57	2
56	2
55	2
56	2
54	2
55	2
46	2
52	2
32	2
44	2
46	2
59	2
46	2
46	2
54	2
66	2
56	2
59	2
57	2
52	2
48	2
44	2
41	2
50	2
48	2
48	2
59	2
34	2
46	2
54	2
55	2
54	2
59	2
44	2
54	2
52	2
66	2
44	2
57	2
39	2
60	2
45	2
41	2
50	2
39	2
43	3
48	3
37	3
58	3
46	3
43	3
44	3
34	3
30	3
50	3
39	3
37	3
55	3
48	3
41	3
39	3
36	3
43	3
50	3
55	3
43	3
60	3
48	3
30	3
43	3
39	3
52	3
39	3
39	3
56	3
59	3
46	3
57	3
50	3
54	3
50	3
60	3
59	3
41	3
48	3
59	3
60	3
56	3
56	NA
51	NA

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185949&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185949&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185949&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'George Udny Yule' @ yule.wessa.net






ANOVA Model
30months ~ maternal-warmth
means45.5484.5071.5227.952

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
30months  ~  maternal-warmth \tabularnewline
means & 45.548 & 4.507 & 1.522 & 7.952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185949&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]30months  ~  maternal-warmth[/C][/ROW]
[ROW][C]means[/C][C]45.548[/C][C]4.507[/C][C]1.522[/C][C]7.952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185949&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185949&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
30months ~ maternal-warmth
means45.5484.5071.5227.952






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
maternal-warmth3656.499218.8333.1720.026
Residuals15610761.47668.984 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
maternal-warmth & 3 & 656.499 & 218.833 & 3.172 & 0.026 \tabularnewline
Residuals & 156 & 10761.476 & 68.984 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185949&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]maternal-warmth[/C][C]3[/C][C]656.499[/C][C]218.833[/C][C]3.172[/C][C]0.026[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]10761.476[/C][C]68.984[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185949&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185949&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)
maternal-warmth3656.499218.8333.1720.026
Residuals15610761.47668.984






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-14.5070.338.6840.029
3-11.522-3.1576.2020.833
NA-17.952-7.65823.5630.55
3-2-2.985-7.1311.1610.245
NA-23.445-12.01418.9040.938
NA-36.43-9.17222.0330.708

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 4.507 & 0.33 & 8.684 & 0.029 \tabularnewline
3-1 & 1.522 & -3.157 & 6.202 & 0.833 \tabularnewline
NA-1 & 7.952 & -7.658 & 23.563 & 0.55 \tabularnewline
3-2 & -2.985 & -7.131 & 1.161 & 0.245 \tabularnewline
NA-2 & 3.445 & -12.014 & 18.904 & 0.938 \tabularnewline
NA-3 & 6.43 & -9.172 & 22.033 & 0.708 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185949&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]4.507[/C][C]0.33[/C][C]8.684[/C][C]0.029[/C][/ROW]
[ROW][C]3-1[/C][C]1.522[/C][C]-3.157[/C][C]6.202[/C][C]0.833[/C][/ROW]
[ROW][C]NA-1[/C][C]7.952[/C][C]-7.658[/C][C]23.563[/C][C]0.55[/C][/ROW]
[ROW][C]3-2[/C][C]-2.985[/C][C]-7.131[/C][C]1.161[/C][C]0.245[/C][/ROW]
[ROW][C]NA-2[/C][C]3.445[/C][C]-12.014[/C][C]18.904[/C][C]0.938[/C][/ROW]
[ROW][C]NA-3[/C][C]6.43[/C][C]-9.172[/C][C]22.033[/C][C]0.708[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185949&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185949&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
2-14.5070.338.6840.029
3-11.522-3.1576.2020.833
NA-17.952-7.65823.5630.55
3-2-2.985-7.1311.1610.245
NA-23.445-12.01418.9040.938
NA-36.43-9.17222.0330.708






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.7120.546
156 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.712 & 0.546 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185949&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]3[/C][C]0.712[/C][C]0.546[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185949&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185949&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)
Group30.7120.546
156


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')