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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 computationThu, 07 Nov 2013 06:35:04 -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/2013/Nov/07/t1383824202wfenz0ssy56ukbk.htm/, Retrieved Thu, 02 May 2024 23:31:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223204, Retrieved Thu, 02 May 2024 23:31:09 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [One-way ANOVA] [2013-11-07 11:35:04] [67f3950ed3b2313b1c71621235f91b37] [Current]
- R  D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-10 19:12:37] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
36	88
56	94
48	90
32	73
44	68
39	80
34	86
41	86
50	91
39	79
62	96
52	92
37	72
50	96
41	70
55	86
41	87
56	88
39	79
52	90
46	95
44	85	
41	90
50	115
50	84
44	79
52	94
54	97
44	86
52	111
37	87
52	98
50	87
36	68
50	88
52	82
55	111
31	75
36	94
49	95
42	80
37	95
41	68
30	94
52	88
30	84	
44	101
66	98
48	78
43	109
57	102
46	81
54	97
48	75
48	97
	
62	101
58	101
58	95
62	95	
46	95
34	90
66	107
52	92
55	86
55	70
57	95
56	96
55	91
56	87
54	92
55	97
46	102
52	91
32	68
44	88
46	97
59	90
46	101
46	94
54	101
66	109
56	100
59	103
57	94
52	97
48	85
44	75
41	77
50	87
48	78
48	108
59	97
34	105
46	106
54	107
55	95
54	107
59	115
44	101
54	85
52	90
66	115
44	95
57	97
39	112
60	97
45	77
41	90
50	94
39	103
43	77
48	98
37	90
58	111
46	77
43	88
44	75
34	92
30	78
50	106
39	80
37	87
55	92	
41	111
39	86
36	85
43	90
50	101
55	94
43	86
60	86
48	90
30	75
43	86
39	91
52	97
39	91
39	70
56	98
59	96
46	95
57	100
50	95
54	97
50	97
60	92
59	115
41	88
48	87
59	100
60	98
56	102
51	96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.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=223204&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]'Herman Ole Andreas Wold' @ wold.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=223204&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223204&T=0

As an alternative you can also use a 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'Herman Ole Andreas Wold' @ wold.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
MC30VRB ~ WISCRY7V
means57.33351.14353493448584854.551.53958.538.2545373239.443.754240.6674046524045.54645.5714645.54751.16747.755055.653.41756.4

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  WISCRY7V

 \tabularnewline
means & 57.333 & 51.143 & 53 & 49 & 34 & 48 & 58 & 48 & 54.5 & 51.5 & 39 & 58.5 & 38.25 & 45 & 37 & 32 & 39.4 & 43.75 & 42 & 40.667 & 40 & 46 & 52 & 40 & 45.5 & 46 & 45.571 & 46 & 45.5 & 47 & 51.167 & 47.75 & 50 & 55.6 & 53.417 & 56.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223204&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]MC30VRB  ~  WISCRY7V

[/C][/ROW]
[ROW][C]means[/C][C]57.333[/C][C]51.143[/C][C]53[/C][C]49[/C][C]34[/C][C]48[/C][C]58[/C][C]48[/C][C]54.5[/C][C]51.5[/C][C]39[/C][C]58.5[/C][C]38.25[/C][C]45[/C][C]37[/C][C]32[/C][C]39.4[/C][C]43.75[/C][C]42[/C][C]40.667[/C][C]40[/C][C]46[/C][C]52[/C][C]40[/C][C]45.5[/C][C]46[/C][C]45.571[/C][C]46[/C][C]45.5[/C][C]47[/C][C]51.167[/C][C]47.75[/C][C]50[/C][C]55.6[/C][C]53.417[/C][C]56.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223204&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223204&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
MC30VRB ~ WISCRY7V
means57.33351.14353493448584854.551.53958.538.2545373239.443.754240.6674046524045.54645.5714645.54751.16747.755055.653.41756.4







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
WISCRY7V 36359602.7459988.965181.020
Residuals1176456.25555.182

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
WISCRY7V

 & 36 & 359602.745 & 9988.965 & 181.02 & 0 \tabularnewline
Residuals & 117 & 6456.255 & 55.182 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223204&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]WISCRY7V

[/C][C]36[/C][C]359602.745[/C][C]9988.965[/C][C]181.02[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]117[/C][C]6456.255[/C][C]55.182[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223204&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223204&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
WISCRY7V 36359602.7459988.965181.020
Residuals1176456.25555.182







Must Include Intercept to use Tukey Test

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223204&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223204&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223204&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Must Include Intercept to use Tukey Test







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group350.8710.673
117

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 35 & 0.871 & 0.673 \tabularnewline
  & 117 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223204&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]35[/C][C]0.871[/C][C]0.673[/C][/ROW]
[ROW][C] [/C][C]117[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223204&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223204&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group350.8710.673
117



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
R code (references can be found in the software module):
par3 <- 'FALSE'
par2 <- '2'
par1 <- '1'
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){
'Tukey Plot'
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<-leveneTest(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')