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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 computationFri, 02 Nov 2012 10:14:48 -0400
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/02/t135186575965arvsxcrf88b1u.htm/, Retrieved Sun, 01 Oct 2023 15:31:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185618, Retrieved Sun, 01 Oct 2023 15:31:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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)] [WS5 Ex 1 age,words,7] [2012-11-02 11:00:30] [74be16979710d4c4e7c6647856088456]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Ex 1 Age + 30...] [2012-11-02 12:22:45] [74be16979710d4c4e7c6647856088456]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Ex 1 Age + yr7] [2012-11-02 12:44:44] [74be16979710d4c4e7c6647856088456]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Ex 2 mIQ, cviq] [2012-11-02 14:14:48] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 ex 2 miq, cvi...] [2012-11-02 14:41:14] [74be16979710d4c4e7c6647856088456]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185618&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]3 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=185618&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185618&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
MC30VRB ~ MVRBIQ0
means46.9780.7564.54

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MVRBIQ0 \tabularnewline
means & 46.978 & 0.756 & 4.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185618&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]46.978[/C][C]0.756[/C][C]4.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185618&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185618&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
means46.9780.7564.54






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ02383.067191.5342.6530.074
Residuals14910755.13772.182 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 2 & 383.067 & 191.534 & 2.653 & 0.074 \tabularnewline
Residuals & 149 & 10755.137 & 72.182 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185618&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]383.067[/C][C]191.534[/C][C]2.653[/C][C]0.074[/C][/ROW]
[ROW][C]Residuals[/C][C]149[/C][C]10755.137[/C][C]72.182[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185618&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185618&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)
MVRBIQ02383.067191.5342.6530.074
Residuals14910755.13772.182






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10.756-2.9744.4860.881
3-14.54-0.3369.4160.074
3-23.784-0.6998.2680.116

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 0.756 & -2.974 & 4.486 & 0.881 \tabularnewline
3-1 & 4.54 & -0.336 & 9.416 & 0.074 \tabularnewline
3-2 & 3.784 & -0.699 & 8.268 & 0.116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185618&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]0.756[/C][C]-2.974[/C][C]4.486[/C][C]0.881[/C][/ROW]
[ROW][C]3-1[/C][C]4.54[/C][C]-0.336[/C][C]9.416[/C][C]0.074[/C][/ROW]
[ROW][C]3-2[/C][C]3.784[/C][C]-0.699[/C][C]8.268[/C][C]0.116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185618&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185618&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
2-10.756-2.9744.4860.881
3-14.54-0.3369.4160.074
3-23.784-0.6998.2680.116






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.0010.999
149 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.001 & 0.999 \tabularnewline
  & 149 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185618&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]149[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185618&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185618&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
149


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; 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')