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Description of Statistical Computation

Author's title

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 10:57:36 -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/t1322582269f48pz29in32vuyn.htm/, Retrieved Thu, 18 Apr 2024 19:03:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148571, Retrieved Thu, 18 Apr 2024 19:03:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

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]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [MATERNAL WARMTH A...] [2011-11-29 15:57:36] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3	1
6	1
8	2
8	2
7	2
5	1
7	2
8	2
9	3
9	3
3	1
9	3
7	2
9	3
8	2
6	1
7	2
8	2
9	3
7	2
6	1
8	2
7	2
7	2
8	2
9	3
9	3
7	2
4	1
7	2
7	2
9	3
7	2
9	3
10	3
5	1
6	1
9	3
9	3
8	2
6	1
6	1
5	1
8	2
8	2
5	1
6	1
9	3
8	2
4	1
8	2
9	3
7	2
7	2
6	1
9	3
9	3
8	2
4	1
6	1
10	3
8	2
7	2
7	2
8	2
3	1
8	2
10	3
7	2
5	1
10	3
5	1
8	2
9	3
6	1
9	2
8	2
5	1
8	2
3	1
7	2
8	2
10	3
9	3
10	3
9	3
8	2
8	2
8	2
9	3
4	1
6	1
7	2
4	1
9	3
7	2
8	2
0	0
8	2
7	2
7	2
9	3
8	2
8	2
9	3
9	3
10	3
7	2
8	2
5	1
9	3
8	2
7	2
8	2
8	2
7	2
6	1
7	2
7	2
6	1
6	1
7	2
9	3
6	1
10	3
4	1
8	2
7	2
10	3
0	0
5	1
9	3
8	2
9	3
8	2
8	2
9	3
8	2
9	3
7	2
6	1
8	2
6	1
5	1
3	1
6	1
8	2
7	2
8	2
6	1
9	3
9	3
10	3
7	2
5	1
8	2
9	3
8	2
8	2
4	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'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=148571&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=148571&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148571&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
MWARM30 ~ VI
means05.0487.5959.238

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MWARM30  ~  VI \tabularnewline
means & 0 & 5.048 & 7.595 & 9.238 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148571&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MWARM30  ~  VI[/C][/ROW]
[ROW][C]means[/C][C]0[/C][C]5.048[/C][C]7.595[/C][C]9.238[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148571&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148571&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
MWARM30 ~ VI
means05.0487.5959.238






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
VI3483.613161.204342.7930
Residuals15673.3620.47 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
VI & 3 & 483.613 & 161.204 & 342.793 & 0 \tabularnewline
Residuals & 156 & 73.362 & 0.47 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148571&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]VI[/C][C]3[/C][C]483.613[/C][C]161.204[/C][C]342.793[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]73.362[/C][C]0.47[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148571&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148571&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)
VI3483.613161.204342.7930
Residuals15673.3620.47






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-05.0483.7596.3370
2-07.5956.3188.8710
3-09.2387.94910.5270
2-12.5472.2032.8910
3-14.193.8024.5790
3-21.6441.2991.9880

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 5.048 & 3.759 & 6.337 & 0 \tabularnewline
2-0 & 7.595 & 6.318 & 8.871 & 0 \tabularnewline
3-0 & 9.238 & 7.949 & 10.527 & 0 \tabularnewline
2-1 & 2.547 & 2.203 & 2.891 & 0 \tabularnewline
3-1 & 4.19 & 3.802 & 4.579 & 0 \tabularnewline
3-2 & 1.644 & 1.299 & 1.988 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148571&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]5.048[/C][C]3.759[/C][C]6.337[/C][C]0[/C][/ROW]
[ROW][C]2-0[/C][C]7.595[/C][C]6.318[/C][C]8.871[/C][C]0[/C][/ROW]
[ROW][C]3-0[/C][C]9.238[/C][C]7.949[/C][C]10.527[/C][C]0[/C][/ROW]
[ROW][C]2-1[/C][C]2.547[/C][C]2.203[/C][C]2.891[/C][C]0[/C][/ROW]
[ROW][C]3-1[/C][C]4.19[/C][C]3.802[/C][C]4.579[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]1.644[/C][C]1.299[/C][C]1.988[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148571&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148571&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
1-05.0483.7596.3370
2-07.5956.3188.8710
3-09.2387.94910.5270
2-12.5472.2032.8910
3-14.193.8024.5790
3-21.6441.2991.9880






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group311.5010
156 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 11.501 & 0 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148571&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]11.501[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148571&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148571&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)
Group311.5010
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')