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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 computationFri, 25 Nov 2011 09:14:04 -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/25/t1322230458l8ndkl1y2lkcqnn.htm/, Retrieved Fri, 01 Nov 2024 01:03:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147318, Retrieved Fri, 01 Nov 2024 01:03:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact194

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)] [verbal iq 30 months] [2011-11-24 12:52:00] [a2de6508349022a1eb68cf1e7e46129d]
-   PD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [verbal iq 30 months] [2011-11-24 13:00:43] [a2de6508349022a1eb68cf1e7e46129d]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mverbal iq 30 months] [2011-11-25 13:12:08] [a2de6508349022a1eb68cf1e7e46129d]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mwarm iq30] [2011-11-25 14:07:37] [a2de6508349022a1eb68cf1e7e46129d]
-   P                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mwarm year7] [2011-11-25 14:14:04] [a24b35eb27a1a581879383db35460db1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	36	88
2	56	94
2	48	90
2	32	73
1	44	68
2	39	80
2	34	86
3	41	86
3	50	91
1	39	79
3	62	96
2	52	92
3	37	72
2	50	96
1	41	70
2	55	86
2	41	87
3	56	88
2	39	79
1	52	90
2	46	95
2	44	85
2	41	90
3	50	115
3	50	84
2	44	79
1	52	94
2	54	97
2	44	86
3	52	111
2	37	87
3	52	98
3	50	87
1	36	68
1	50	88
3	52	82
3	55	111
2	31	75
1	36	94
1	49	95
1	42	80
2	37	95
2	41	68
1	30	94
1	52	88
3	30	84
1	44	101
2	66	98
3	48	78
2	43	109
2	57	102
1	46	81
3	54	97
3	48	75
2	48	97
1	62	101
3	58	101
2	58	95
2	62	95
2	46	95
1	34	90
2	66	107
3	52	92
2	55	86
1	55	70
3	57	95
1	56	96
2	55	91
3	56	87
1	54	92
3	55	97
2	46	102
1	52	91
2	32	68
1	44	88
2	46	97
2	59	90
3	46	101
3	46	94
3	54	101
3	66	109
2	56	100
2	59	103
2	57	94
3	52	97
1	48	85
1	44	75
2	41	77
1	50	87
3	48	78
2	48	108
2	59	97
2	46	106
2	54	107
2	55	95
3	54	107
2	59	115
2	44	101
3	54	85
3	52	90
3	66	115
2	44	95
2	57	97
1	39	112
3	60	97
2	45	77
2	41	90
2	50	94
2	39	103
2	43	77
1	48	98
2	37	90
2	58	111
1	46	77
1	43	88
2	44	75
3	34	92
1	30	78
3	50	106
1	39	80
2	37	87
2	55	92
1	39	86
3	36	85
2	43	90
3	50	101
2	55	94
2	43	86
3	60	86
2	48	90
3	30	75
2	43	86
1	39	91
2	52	97
1	39	91
1	39	70
1	56	98
1	59	96
2	46	95
2	57	100
2	50	95
1	54	97
3	50	97
3	60	92
3	59	115
2	41	88
1	48	87
2	59	100
3	60	98
2	56	102
1	51	96

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147318&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147318&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147318&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'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
WISCRY7V ~ MWARM30
means87.454.8116.55

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MWARM30 \tabularnewline
means & 87.45 & 4.811 & 6.55 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147318&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]87.45[/C][C]4.811[/C][C]6.55[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147318&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147318&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
WISCRY7V ~ MWARM30
means87.454.8116.55






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM302958.412479.2064.410.014
Residuals14816081.204108.657 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 2 & 958.412 & 479.206 & 4.41 & 0.014 \tabularnewline
Residuals & 148 & 16081.204 & 108.657 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147318&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]MWARM30[/C][C]2[/C][C]958.412[/C][C]479.206[/C][C]4.41[/C][C]0.014[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]16081.204[/C][C]108.657[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147318&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147318&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)
MWARM302958.412479.2064.410.014
Residuals14816081.204108.657






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-14.811-0.0939.7150.056
3-16.551.09812.0020.014
3-21.739-3.0916.5690.671

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 4.811 & -0.093 & 9.715 & 0.056 \tabularnewline
3-1 & 6.55 & 1.098 & 12.002 & 0.014 \tabularnewline
3-2 & 1.739 & -3.091 & 6.569 & 0.671 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147318&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]4.811[/C][C]-0.093[/C][C]9.715[/C][C]0.056[/C][/ROW]
[ROW][C]3-1[/C][C]6.55[/C][C]1.098[/C][C]12.002[/C][C]0.014[/C][/ROW]
[ROW][C]3-2[/C][C]1.739[/C][C]-3.091[/C][C]6.569[/C][C]0.671[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147318&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147318&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
2-14.811-0.0939.7150.056
3-16.551.09812.0020.014
3-21.739-3.0916.5690.671






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.6690.514
148 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.669 & 0.514 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147318&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]0.669[/C][C]0.514[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147318&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147318&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)
Group20.6690.514
148


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 3 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 3 ; 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')