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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, 13 Nov 2014 13:30:38 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/13/t141588549868t0wk2lzto02pr.htm/, Retrieved Wed, 15 May 2024 19:26:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=254347, Retrieved Wed, 15 May 2024 19:26:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
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)] [-] [2014-11-13 13:15:19] [2ec76ed569dd0e1337cbe5bca4946b7e]
-    D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [-] [2014-11-13 13:30:38] [06f8ade0bc20bf5f0ea4e30879dd3bdb] [Current]
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Dataseries X:
67	0
86	88
86	94
103	90
74	73
63	68
82	80
93	86
77	86
111	91
71	79
103	96
89	92
75	72
88	96
84	70
85	86
70	87
104	88
88	79
77	90
77	95
72	85
70	0
83	90
110	115
91	84
80	79
91	94
86	97
85	86
107	111
93	87
87	98
84	87
73	68
84	88
86	82
99	111
75	75
87	94
79	95
82	80
95	95
84	68
85	94
95	88
63	84
78	0
85	101
86	98
75	78
98	109
71	102
63	81
71	97
84	75
81	97
93	0
79	101
63	101
93	95
92	95
93	0
83	95
80	90
111	107
92	92
79	86
69	70
83	95
80	96
91	91
97	87
85	92
85	97
99	102
67	91
87	68
68	88
81	97
80	90
93	101
93	94
102	101
104	109
90	100
85	103
92	94
82	97
85	85
89	75
77	77
79	87
76	78
101	108
81	97
92	105
89	106
81	107
77	95
95	107
85	115
81	101
76	85
93	90
104	115
89	95
76	97
77	112
71	97
79	77
89	90
81	94
99	103
81	77
84	98
85	90
111	111
78	77
111	88
78	75
87	92
92	78
93	106
70	80
84	87
75	92
105	0
96	111
85	86
87	85
75	90
103	101
86	94
77	86
74	86
74	90
76	75
83	86
101	91
83	97
92	91
74	70
87	98
71	96
79	95
83	100
80	95
90	97
80	97
96	92
109	115
98	88
85	87
83	100
86	98
72	102
83	0
75	96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254347&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254347&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254347&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







ANOVA Model
WISCRY7V ~ MVRBIQ0
means99.510195.667104011111511599.2583.545.5887055.66794.293.56879.7583.83383.7591.57150.66790.16791.16795.71485.66782.87581.85793.59389.16787.591.698.589.66792.573.22296.667101.58798.5105.333

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MVRBIQ0 \tabularnewline
means & 99.5 & 101 & 95.667 & 104 & 0 & 111 & 115 & 115 & 99.25 & 83.5 & 45.5 & 88 & 70 & 55.667 & 94.2 & 93.5 & 68 & 79.75 & 83.833 & 83.75 & 91.571 & 50.667 & 90.167 & 91.167 & 95.714 & 85.667 & 82.875 & 81.857 & 93.5 & 93 & 89.167 & 87.5 & 91.6 & 98.5 & 89.667 & 92.5 & 73.222 & 96.667 & 101.5 & 87 & 98.5 & 105.333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254347&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]WISCRY7V  ~  MVRBIQ0[/C][/ROW]
[ROW][C]means[/C][C]99.5[/C][C]101[/C][C]95.667[/C][C]104[/C][C]0[/C][C]111[/C][C]115[/C][C]115[/C][C]99.25[/C][C]83.5[/C][C]45.5[/C][C]88[/C][C]70[/C][C]55.667[/C][C]94.2[/C][C]93.5[/C][C]68[/C][C]79.75[/C][C]83.833[/C][C]83.75[/C][C]91.571[/C][C]50.667[/C][C]90.167[/C][C]91.167[/C][C]95.714[/C][C]85.667[/C][C]82.875[/C][C]81.857[/C][C]93.5[/C][C]93[/C][C]89.167[/C][C]87.5[/C][C]91.6[/C][C]98.5[/C][C]89.667[/C][C]92.5[/C][C]73.222[/C][C]96.667[/C][C]101.5[/C][C]87[/C][C]98.5[/C][C]105.333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254347&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254347&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 ~ MVRBIQ0
means99.510195.667104011111511599.2583.545.5887055.66794.293.56879.7583.83383.7591.57150.66790.16791.16795.71485.66782.87581.85793.59389.16787.591.698.589.66792.573.22296.667101.58798.5105.333







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVRBIQ0421259664.31929992.00880.2370
Residuals11844107.681373.794

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVRBIQ0 & 42 & 1259664.319 & 29992.008 & 80.237 & 0 \tabularnewline
Residuals & 118 & 44107.681 & 373.794 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254347&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]42[/C][C]1259664.319[/C][C]29992.008[/C][C]80.237[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]118[/C][C]44107.681[/C][C]373.794[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254347&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254347&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)
MVRBIQ0421259664.31929992.00880.2370
Residuals11844107.681373.794







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=254347&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254347&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254347&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)
Group410.8770.678
118

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 41 & 0.877 & 0.678 \tabularnewline
  & 118 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254347&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]41[/C][C]0.877[/C][C]0.678[/C][/ROW]
[ROW][C] [/C][C]118[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254347&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254347&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)
Group410.8770.678
118



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