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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 computationMon, 05 Nov 2012 19:14:50 -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/2012/Nov/05/t1352161015tm6d4upzlcg4xj0.htm/, Retrieved Sun, 05 Feb 2023 23:18:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=186403, Retrieved Sun, 05 Feb 2023 23:18:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84
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)] [CARE data] [2012-11-06 00:03:19] [39d2f47f31fef288e1c3cef9a486b324]
-   P               [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE data] [2012-11-06 00:14:50] [ba64bc3677ce2e3ca44b42196f7d02ba] [Current]
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Dataseries X:
88	36
94	56
90	48
73	32
68	44
80	39
86	34
86	41
91	50
79	39
96	62
92	52
72	37
96	50
70	41
86	55
87	41
88	56
79	39
90	52
95	46
85	44
	48
90	41
115	50
84	50
79	44
94	52
97	54
86	44
111	52
87	37
98	52
87	50
68	36
88	50
82	52
111	55
75	31
94	36
95	49
80	42
95	37
68	41
94	30
88	52
84	30
	41
101	44
98	66
78	48
109	43
102	57
81	46
97	54
75	48
97	48
101	62
101	58
95	58
95	62
95	46
90	34
107	66
92	52
86	55
70	55
95	57
96	56
91	55
87	56
92	54
97	55
102	46
91	52
68	32
88	44
97	46
90	59
101	46
94	46
101	54
109	66
100	56
103	59
94	57
97	52
85	48
75	44
77	41
87	50
78	48
108	48
97	59
105	34
106	46
107	54
95	55
107	54
115	59
101	44
85	54
90	52
115	66
95	44
97	57
112	39
97	60
77	45
90	41
94	50
103	39
77	43
98	48
90	37
111	58
77	46
88	43
75	44
92	34
78	30
106	50
80	39
87	37
92	55
	48
111	41
86	39
85	36
90	43
101	50
94	55
86	43
86	60
90	48
75	30
86	43
91	39
97	52
91	39
70	39
98	56
96	59
95	46
100	57
95	50
97	54
97	50
92	60
115	59
88	41
87	48
100	59
98	60
102	56
96	51




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186403&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186403&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186403&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net







ANOVA Model
WISCRY7V ~ MC30VRB
means4743604850.57870.593.25888388.83373.33391.333867794.22288.62594.89298.16788.1439397102.333101.259797.333107.2543.53951.5504950513944.648.333444847.55040.448.55648.7545

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MC30VRB \tabularnewline
means & 47 & 43 & 60 & 48 & 50.5 & 78 & 70.5 & 93.25 & 88 & 83 & 88.833 & 73.333 & 91.333 & 86 & 77 & 94.222 & 88.625 & 94.8 & 92 & 98.167 & 88.143 & 93 & 97 & 102.333 & 101.25 & 97 & 97.333 & 107.25 & 43.5 & 39 & 51.5 & 50 & 49 & 50 & 51 & 39 & 44.6 & 48.333 & 44 & 48 & 47.5 & 50 & 40.4 & 48.5 & 56 & 48.75 & 45 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186403&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]WISCRY7V  ~  MC30VRB[/C][/ROW]
[ROW][C]means[/C][C]47[/C][C]43[/C][C]60[/C][C]48[/C][C]50.5[/C][C]78[/C][C]70.5[/C][C]93.25[/C][C]88[/C][C]83[/C][C]88.833[/C][C]73.333[/C][C]91.333[/C][C]86[/C][C]77[/C][C]94.222[/C][C]88.625[/C][C]94.8[/C][C]92[/C][C]98.167[/C][C]88.143[/C][C]93[/C][C]97[/C][C]102.333[/C][C]101.25[/C][C]97[/C][C]97.333[/C][C]107.25[/C][C]43.5[/C][C]39[/C][C]51.5[/C][C]50[/C][C]49[/C][C]50[/C][C]51[/C][C]39[/C][C]44.6[/C][C]48.333[/C][C]44[/C][C]48[/C][C]47.5[/C][C]50[/C][C]40.4[/C][C]48.5[/C][C]56[/C][C]48.75[/C][C]45[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186403&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186403&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
WISCRY7V ~ MC30VRB
means4743604850.57870.593.25888388.83373.33391.333867794.22288.62594.89298.16788.1439397102.333101.259797.333107.2543.53951.5504950513944.648.333444847.55040.448.55648.7545







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MC30VRB47961417.34620455.688186.6510
Residuals10911945.654109.593

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MC30VRB & 47 & 961417.346 & 20455.688 & 186.651 & 0 \tabularnewline
Residuals & 109 & 11945.654 & 109.593 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186403&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]MC30VRB[/C][C]47[/C][C]961417.346[/C][C]20455.688[/C][C]186.651[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]109[/C][C]11945.654[/C][C]109.593[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186403&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186403&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)
MC30VRB47961417.34620455.688186.6510
Residuals10911945.654109.593







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=186403&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186403&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186403&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)
Group460.8390.746
109

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 46 & 0.839 & 0.746 \tabularnewline
  & 109 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186403&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]46[/C][C]0.839[/C][C]0.746[/C][/ROW]
[ROW][C] [/C][C]109[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186403&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186403&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)
Group460.8390.746
109



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):
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')