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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, 25 Nov 2011 07:47:21 -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/t1322225255h69zbdzgoe7g9y1.htm/, Retrieved Sun, 22 Dec 2024 06:30:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147303, Retrieved Sun, 22 Dec 2024 06:30:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200

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 PD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers Age Gests...] [2011-11-24 13:11:47] [84f9d24ffbb976b91a97c3ec996667ce]
-   P             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers Age Gests...] [2011-11-24 13:16:14] [84f9d24ffbb976b91a97c3ec996667ce]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-25 12:47:21] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-25 13:39:27] [74be16979710d4c4e7c6647856088456]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-25 13:40:38] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	44	68
1	30	84
1	46	81
1	58	101
1	52	91
1	44	88
1	55	70
1	41	87
1	39	80
1	39	79
1	57	102
1	54	97
1	60	97
1	59	96
1	44	85
1	56	102
1	36	68
1	32	73
1	60	86
1	48	90
1	39	70
1	37	72
1	31	75
1	48	78
1	55	92
1	43	90
1	51	96
1	48	78
1	54	85
1	57	97
1	30	75
1	41	86
1	52	90
1	46	95
1	41	77
1	55	95
1	39	112
1	43	86
1	46	77
1	44	75
1	49	95
1	62	101
1	55	86
1	50	87
1	45	77
1	46	95
2	44	79
2	34	90
2	56	96
2	59	90
2	50	95
2	50	97
2	48	97
2	46	97
2	59	97
2	54	107
2	44	101
2	50	94
2	43	77
2	39	80
2	42	80
2	52	97
2	41	90
2	46	95
2	57	95
2	43	86
2	52	97
2	57	100
2	59	100
2	41	70
2	50	87
2	50	88
2	41	68
2	48	75
2	48	98
2	37	87
2	55	86
2	44	86
2	30	94
2	44	101
2	54	92
2	55	97
2	59	103
2	48	85
2	59	115
2	37	90
2	39	86
2	48	87
2	36	88
2	56	94
2	54	97
2	52	82
2	66	98
2	55	94
2	60	98
2	52	98
2	36	94
2	32	68
2	34	92
2	36	85
2	56	98
2	50	96
2	39	79
2	52	92
2	44	75
2	46	106
2	44	95
2	41	90
2	56	100
2	54	97
2	50	84
2	52	94
2	55	91
2	62	95
2	52	92
2	57	94
2	34	105
2	30	78
2	39	91
2	34	86
2	37	87
2	58	95
2	46	101
2	46	94
2	52	90
2	50	106
2	37	95
2	52	88
2	54	107
3	41	111
3	60	92
3	56	87
3	43	109
3	41	88
3	55	111
3	46	102
3	39	103
3	48	108
3	39	91
3	54	101
3	48	90
3	62	96
3	50	101
3	56	88
3	66	109
3	66	115
3	52	111
3	59	115
3	50	115
3	50	91
3	66	107
3	58	111
3	43	88

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'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147303&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147303&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147303&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'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






ANOVA Model
WISCRY7V ~ MVRBIQ0
means86.2395.5815.428

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V
  ~  MVRBIQ0 \tabularnewline
means & 86.239 & 5.58 & 15.428 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147303&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V
  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]86.239[/C][C]5.58[/C][C]15.428[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147303&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147303&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 ~ MVRBIQ0
means86.2395.5815.428






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ023756.9491878.47520.3590
Residuals15013839.99292.267 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 2 & 3756.949 & 1878.475 & 20.359 & 0 \tabularnewline
Residuals & 150 & 13839.992 & 92.267 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147303&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]3756.949[/C][C]1878.475[/C][C]20.359[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]13839.992[/C][C]92.267[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147303&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147303&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)
MVRBIQ023756.9491878.47520.3590
Residuals15013839.99292.267






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-15.581.4019.760.005
3-115.4289.70221.1530
3-29.8474.57715.1170

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 5.58 & 1.401 & 9.76 & 0.005 \tabularnewline
3-1 & 15.428 & 9.702 & 21.153 & 0 \tabularnewline
3-2 & 9.847 & 4.577 & 15.117 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147303&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]5.58[/C][C]1.401[/C][C]9.76[/C][C]0.005[/C][/ROW]
[ROW][C]3-1[/C][C]15.428[/C][C]9.702[/C][C]21.153[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]9.847[/C][C]4.577[/C][C]15.117[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147303&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147303&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
2-15.581.4019.760.005
3-115.4289.70221.1530
3-29.8474.57715.1170






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group22.0880.128
150 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 2.088 & 0.128 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147303&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]2.088[/C][C]0.128[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147303&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147303&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)
Group22.0880.128
150


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')