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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, 18 Nov 2014 13:47:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/18/t14163186968zpoavci1kl6da0.htm/, Retrieved Sun, 19 May 2024 15:21:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=256066, Retrieved Sun, 19 May 2024 15:21:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [maternal age] [2014-11-17 11:39:53] [641a0532220e648aec0292d323d571dc]
- R PD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [maternaliq] [2014-11-18 13:47:42] [4ec7bf9422a703085f65cf71608e4cf5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	67	1
36	86	2
56	86	2
48	103	3
32	74	1
44	63	1
39	82	2
34	93	2
41	77	1
50	111	3
39	71	1
62	103	3
52	89	2
37	75	1
50	88	2
41	84	2
55	85	2
41	70	1
56	104	3
39	88	2
52	77	1
46	77	1
44	72	1
48	70	1
41	83	2
50	110	3
50	91	2
44	80	2
52	91	2
54	86	2
44	85	2
52	107	3
37	93	2
52	87	2
50	84	2
36	73	1
50	84	2
52	86	2
55	99	3
31	75	1
36	87	2
49	79	1
42	82	2
37	95	3
41	84	2
30	85	2
52	95	3
30	63	1
41	78	1
44	85	2
66	86	2
48	75	1
43	98	3
57	71	1
46	63	1
54	71	1
48	84	2
48	81	2
52	93	2
62	79	1
58	63	1
58	93	2
62	92	2
48	93	2
46	83	2
34	80	2
66	111	3
52	92	2
55	79	1
55	69	1
57	83	2
56	80	2
55	91	2
56	97	3
54	85	2
55	85	2
46	99	3
52	67	1
32	87	2
44	68	1
46	81	2
59	80	2
46	93	2
46	93	2
54	102	3
66	104	3
56	90	2
59	85	2
57	92	2
52	82	2
48	85	2
44	89	2
41	77	1
50	79	1
48	76	1
48	101	3
59	81	2
34	92	2
46	89	2
54	81	2
55	77	1
54	95	3
59	85	2
44	81	2
54	76	1
52	93	2
66	104	3
44	89	2
57	76	1
39	77	1
60	71	1
45	79	1
41	89	2
50	81	2
39	99	3
43	81	2
48	84	2
37	85	2
58	111	3
46	78	1
43	111	3
44	78	1
34	87	2
30	92	2
50	93	2
39	70	1
37	84	2
55	75	1
48	105	3
41	96	3
39	85	2
36	87	2
43	75	1
50	103	3
55	86	2
43	77	1
60	74	1
48	74	1
30	76	1
43	83	2
39	101	3
52	83	2
39	92	2
39	74	1
56	87	2
59	71	1
46	79	1
57	83	2
50	80	2
54	90	2
50	80	2
60	96	3
59	109	3
41	98	3
48	85	2
59	83	2
60	86	2
56	72	1
56	83	2
51	75	1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256066&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256066&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256066&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net






ANOVA Model
verbalIQ ~ MaternalIQgroup
means46.6531.2144.74

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
verbalIQ  ~  MaternalIQgroup \tabularnewline
means & 46.653 & 1.214 & 4.74 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256066&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]verbalIQ  ~  MaternalIQgroup[/C][/ROW]
[ROW][C]means[/C][C]46.653[/C][C]1.214[/C][C]4.74[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256066&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256066&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
verbalIQ ~ MaternalIQgroup
means46.6531.2144.74






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MaternalIQgroup2410.652205.3262.9290.056
Residuals15711007.32370.11 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MaternalIQgroup & 2 & 410.652 & 205.326 & 2.929 & 0.056 \tabularnewline
Residuals & 157 & 11007.323 & 70.11 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256066&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]MaternalIQgroup[/C][C]2[/C][C]410.652[/C][C]205.326[/C][C]2.929[/C][C]0.056[/C][/ROW]
[ROW][C]Residuals[/C][C]157[/C][C]11007.323[/C][C]70.11[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256066&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256066&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)
MaternalIQgroup2410.652205.3262.9290.056
Residuals15711007.32370.11






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-11.214-2.3554.7840.7
3-14.740.0469.4330.047
3-23.525-0.8057.8550.135

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 1.214 & -2.355 & 4.784 & 0.7 \tabularnewline
3-1 & 4.74 & 0.046 & 9.433 & 0.047 \tabularnewline
3-2 & 3.525 & -0.805 & 7.855 & 0.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256066&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]1.214[/C][C]-2.355[/C][C]4.784[/C][C]0.7[/C][/ROW]
[ROW][C]3-1[/C][C]4.74[/C][C]0.046[/C][C]9.433[/C][C]0.047[/C][/ROW]
[ROW][C]3-2[/C][C]3.525[/C][C]-0.805[/C][C]7.855[/C][C]0.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256066&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256066&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
2-11.214-2.3554.7840.7
3-14.740.0469.4330.047
3-23.525-0.8057.8550.135






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.0010.999
157 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.001 & 0.999 \tabularnewline
  & 157 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256066&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]0.001[/C][C]0.999[/C][/ROW]
[ROW][C] [/C][C]157[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256066&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256066&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)
Group20.0010.999
157


Figures (Output of Computation)

Input Parameters & R Code

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):
par3 <- 'TRUE'
par2 <- '3'
par1 <- '1'
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){
'Tukey Plot'
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<-leveneTest(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')