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Description of Statistical Computation

Author's title

Does The Mother's verbal IQ have an impact on the child's verbal IQ in year...

Author*Unverified author*
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 09:53:56 -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/t1322578816qr72auifuxoex4q.htm/, Retrieved Fri, 19 Apr 2024 09:22:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148466, Retrieved Fri, 19 Apr 2024 09:22:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

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  D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mother's verbal I...] [2011-11-24 13:49:05] [5934aceae8cf147bda5be230722b868c]
-   PD              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Does The Mother's...] [2011-11-29 14:53:56] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	67
2	86
2	86
2	103
1	74
1	63
1	82
2	93
2	77
2	111
1	71
3	103
2	89
1	75
3	88
1	84
2	85
2	70
2	104
1	88
2	77
2	77
2	72
0	70
2	83
3	110
2	91
1	80
2	91
2	86
2	85
3	107
2	93
3	87
2	84
1	73
2	84
2	86
3	99
1	75
2	87
2	79
1	82
2	95
1	84
2	85
2	95
2	63
0	78
3	85
3	86
2	75
3	98
3	71
2	63
3	71
1	84
3	81
0	93
3	79
3	63
2	93
2	92
0	93
2	83
2	80
3	111
2	92
2	79
1	69
2	83
3	80
2	91
2	97
2	85
3	85
3	99
2	67
1	87
2	68
3	81
2	80
3	93
2	93
3	102
3	104
3	90
3	85
2	92
3	82
2	85
1	89
1	77
2	79
1	76
3	101
3	81
3	92
3	89
3	81
2	77
3	95
3	85
3	81
2	76
2	93
3	104
2	89
3	76
3	77
3	71
1	79
2	89
2	81
3	99
1	81
3	84
2	85
3	111
1	78
2	111
1	78
2	87
1	92
3	93
1	70
2	84
2	75
0	105
3	96
2	85
2	87
2	75
3	103
2	86
1	77
1	74
2	74
1	76
2	83
2	101
3	83
2	92
1	74
3	87
3	71
2	79
3	83
2	80
3	90
3	80
2	96
3	109
2	98
2	85
3	83
3	86
3	72
0	83
3	75

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'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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148466&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148466&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148466&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'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
MVRNIQ0 ~ VI7C
means84.143-5.8571.2374.339

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MVRNIQ0  ~  VI7C \tabularnewline
means & 84.143 & -5.857 & 1.237 & 4.339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148466&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MVRNIQ0  ~  VI7C[/C][/ROW]
[ROW][C]means[/C][C]84.143[/C][C]-5.857[/C][C]1.237[/C][C]4.339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148466&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148466&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
MVRNIQ0 ~ VI7C
means84.143-5.8571.2374.339






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
VI7C31929.458643.1536.1570.001
Residuals15616294.785104.454 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
VI7C & 3 & 1929.458 & 643.153 & 6.157 & 0.001 \tabularnewline
Residuals & 156 & 16294.785 & 104.454 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148466&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]VI7C[/C][C]3[/C][C]1929.458[/C][C]643.153[/C][C]6.157[/C][C]0.001[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]16294.785[/C][C]104.454[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148466&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148466&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)
VI7C31929.458643.1536.1570.001
Residuals15616294.785104.454






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-5.857-17.0735.3590.529
2-01.237-9.27711.7520.99
3-04.339-6.32315.0010.716
2-17.0951.17213.0170.012
3-110.1964.01516.3770
3-23.101-1.6917.8940.337

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -5.857 & -17.073 & 5.359 & 0.529 \tabularnewline
2-0 & 1.237 & -9.277 & 11.752 & 0.99 \tabularnewline
3-0 & 4.339 & -6.323 & 15.001 & 0.716 \tabularnewline
2-1 & 7.095 & 1.172 & 13.017 & 0.012 \tabularnewline
3-1 & 10.196 & 4.015 & 16.377 & 0 \tabularnewline
3-2 & 3.101 & -1.691 & 7.894 & 0.337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148466&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]1-0[/C][C]-5.857[/C][C]-17.073[/C][C]5.359[/C][C]0.529[/C][/ROW]
[ROW][C]2-0[/C][C]1.237[/C][C]-9.277[/C][C]11.752[/C][C]0.99[/C][/ROW]
[ROW][C]3-0[/C][C]4.339[/C][C]-6.323[/C][C]15.001[/C][C]0.716[/C][/ROW]
[ROW][C]2-1[/C][C]7.095[/C][C]1.172[/C][C]13.017[/C][C]0.012[/C][/ROW]
[ROW][C]3-1[/C][C]10.196[/C][C]4.015[/C][C]16.377[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]3.101[/C][C]-1.691[/C][C]7.894[/C][C]0.337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148466&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148466&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
1-0-5.857-17.0735.3590.529
2-01.237-9.27711.7520.99
3-04.339-6.32315.0010.716
2-17.0951.17213.0170.012
3-110.1964.01516.3770
3-23.101-1.6917.8940.337






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group33.5690.016
156 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 3.569 & 0.016 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148466&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]3.569[/C][C]0.016[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148466&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148466&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)
Group33.5690.016
156


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; 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')