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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_One Factor ANOVA.wasp

Title produced by software

One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation

Sun, 14 Dec 2014 10:11:30 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/14/t1418551983sneiir97vm90s9a.htm/, Retrieved Thu, 16 May 2024 08:14:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267391, Retrieved Thu, 16 May 2024 08:14:29 +0000

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Original text written by user:

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No (this computation is public)

User-defined keywords

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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)] [opnieuw eerste an...] [2014-12-14 10:11:30] [b3af8a5e2d9bda149808ec07c7827d03] [Current]

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Dataseries X:

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Histogram

Boxplots

NA NA
139 6
NA NA
158 1
128 1
224 5.5
NA NA
105 6.5
159 4.5
167 2
165 5
159 0.5
119 5
NA NA
NA NA
NA NA
163 5.5
NA NA
137 3
NA NA
153 0.5
148 6.5
NA NA
188 7.5
149 5.5
244 4
148 7.5
NA NA
150 4
NA NA
NA NA
NA NA
132 3.5
161 2.5
105 4.5
97 4.5
NA NA
131 6
166 2.5
NA NA
111 0
145 5
162 6.5
163 5
59 6
NA NA
109 5.5
90 1
NA NA
83 6
116 5
42 1
148 5
155 6.5
125 7
116 4.5
NA NA
138 8.5
NA NA
96 7.5
164 3.5
NA NA
NA NA
202 9
NA NA
66 3.5
NA NA
214 6.5
188 7.5
NA NA
NA NA
NA NA
NA NA
99 7.5
NA NA
NA NA
108 6.5
NA NA
NA NA
110 1.5
NA NA
NA NA
NA NA
97 0
NA NA
106 5.5
80 5
NA NA
NA NA
NA NA
74 7
114 0
140 4.5
NA NA
98 1.5
NA NA
126 2.5
98 5.5
95 8
110 1
70 5
NA NA
86 3
130 3
96 8
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
99 5.5
48 0.5
50 7.5
150 9
154 9.5
NA NA
68 7
194 8
NA NA
159 7
NA NA
NA NA
39 9.5
100 4
111 6
138 8
101 5.5
131 9.5
101 7.5
114 7
NA NA
114 8
111 7
75 7
82 6
121 10
32 2.5
NA NA
117 8
71 6
165 8.5
154 6
126 9
NA NA
NA NA
120 5.5
NA NA
NA NA
172 9
NA NA
114 8.5
156 9
NA NA
68 9
89 7.5
167 10
NA NA
NA NA
NA NA
NA NA
87 8.5
NA NA
2 10
NA NA
49 6.5
NA NA
96 8.5
NA NA
NA NA
100 8
NA NA
141 7
165 7.5
165 7.5
110 9.5
118 6
NA NA
146 7
NA NA
NA NA
NA NA
155 10
NA NA
147 3.5
NA NA
NA NA
NA NA
NA NA
61 6.5
60 6.5
109 8.5
68 4
NA NA
NA NA
73 8.5
NA NA
NA NA
NA NA
NA NA
220 10
65 8
NA NA
NA NA
122 5
NA NA
44 4.5
52 8.5
NA NA
101 8.5
42 7.5
152 7.5
NA NA
NA NA
NA NA
103 5.5
96 8.5
175 9.5
57 7
NA NA
NA NA
NA NA
110 6.5
131 6.5
NA NA
NA NA
NA NA
86 10
121 10
NA NA
NA NA
NA NA
88 7.5
168 4.5
94 4.5
51 0.5
NA NA
145 4.5
66 5.5
85 5
NA NA
NA NA
102 8
NA NA
86 6.5
114 8
NA NA
119 5.5
NA NA
132 5
142 3.5
NA NA
94 9
NA NA
166 5
NA NA
64 3
NA NA
NA NA
105 0.5
49 6.5
NA NA
95 4.5
102 8
NA NA
63 7.5
NA NA
NA NA
117 9.5
57 6.5
NA NA
73 6
NA NA
NA NA
105 8
NA NA
NA NA

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	120 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 120 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267391&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]120 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267391&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267391&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	120 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

ANOVA Model
examenscore_mannen ~ LFM_mannen
means	6	1.167	2	-0.5	-1.125	-0.5	0.5	1	-1.375	-1.667	0.3	-1.25	2.75	0	-0.75	-0.5	4	-1	1	-0.25	-5	-3	1.333	-1.75	-3	2.25	0	-1.5	1	-2.5	-1.25	1	-2.5	0.333	-0.5	0.5	1.5	-5.5	1.75	2.25	3	-5	-2	-3.5	0.5	-0.75	-2.5	1.125	-2.25	0	-1.5	3	3.5	1.5	2	4	3	0.5	4	-0.5	-2	-3.5	3.5	-1.75	-1.5	-5.5	0.5	1.5	-5.5	2.5	0.75	0	0.5	0.5	1.5	-3	2	-1.5	0.667	-1	0	1.25	1	1	-1	0	0	-1	0.5	2.5	1.5	1.5	-5	0.75	0.25	2.125	-3.75	-2.5	0.5

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
examenscore_mannen  ~  LFM_mannen \tabularnewline
means & 6 & 1.167 & 2 & -0.5 & -1.125 & -0.5 & 0.5 & 1 & -1.375 & -1.667 & 0.3 & -1.25 & 2.75 & 0 & -0.75 & -0.5 & 4 & -1 & 1 & -0.25 & -5 & -3 & 1.333 & -1.75 & -3 & 2.25 & 0 & -1.5 & 1 & -2.5 & -1.25 & 1 & -2.5 & 0.333 & -0.5 & 0.5 & 1.5 & -5.5 & 1.75 & 2.25 & 3 & -5 & -2 & -3.5 & 0.5 & -0.75 & -2.5 & 1.125 & -2.25 & 0 & -1.5 & 3 & 3.5 & 1.5 & 2 & 4 & 3 & 0.5 & 4 & -0.5 & -2 & -3.5 & 3.5 & -1.75 & -1.5 & -5.5 & 0.5 & 1.5 & -5.5 & 2.5 & 0.75 & 0 & 0.5 & 0.5 & 1.5 & -3 & 2 & -1.5 & 0.667 & -1 & 0 & 1.25 & 1 & 1 & -1 & 0 & 0 & -1 & 0.5 & 2.5 & 1.5 & 1.5 & -5 & 0.75 & 0.25 & 2.125 & -3.75 & -2.5 & 0.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267391&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]examenscore_mannen  ~  LFM_mannen[/C][/ROW]
[ROW][C]means[/C][C]6[/C][C]1.167[/C][C]2[/C][C]-0.5[/C][C]-1.125[/C][C]-0.5[/C][C]0.5[/C][C]1[/C][C]-1.375[/C][C]-1.667[/C][C]0.3[/C][C]-1.25[/C][C]2.75[/C][C]0[/C][C]-0.75[/C][C]-0.5[/C][C]4[/C][C]-1[/C][C]1[/C][C]-0.25[/C][C]-5[/C][C]-3[/C][C]1.333[/C][C]-1.75[/C][C]-3[/C][C]2.25[/C][C]0[/C][C]-1.5[/C][C]1[/C][C]-2.5[/C][C]-1.25[/C][C]1[/C][C]-2.5[/C][C]0.333[/C][C]-0.5[/C][C]0.5[/C][C]1.5[/C][C]-5.5[/C][C]1.75[/C][C]2.25[/C][C]3[/C][C]-5[/C][C]-2[/C][C]-3.5[/C][C]0.5[/C][C]-0.75[/C][C]-2.5[/C][C]1.125[/C][C]-2.25[/C][C]0[/C][C]-1.5[/C][C]3[/C][C]3.5[/C][C]1.5[/C][C]2[/C][C]4[/C][C]3[/C][C]0.5[/C][C]4[/C][C]-0.5[/C][C]-2[/C][C]-3.5[/C][C]3.5[/C][C]-1.75[/C][C]-1.5[/C][C]-5.5[/C][C]0.5[/C][C]1.5[/C][C]-5.5[/C][C]2.5[/C][C]0.75[/C][C]0[/C][C]0.5[/C][C]0.5[/C][C]1.5[/C][C]-3[/C][C]2[/C][C]-1.5[/C][C]0.667[/C][C]-1[/C][C]0[/C][C]1.25[/C][C]1[/C][C]1[/C][C]-1[/C][C]0[/C][C]0[/C][C]-1[/C][C]0.5[/C][C]2.5[/C][C]1.5[/C][C]1.5[/C][C]-5[/C][C]0.75[/C][C]0.25[/C][C]2.125[/C][C]-3.75[/C][C]-2.5[/C][C]0.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267391&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267391&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
examenscore_mannen ~ LFM_mannen
means	6	1.167	2	-0.5	-1.125	-0.5	0.5	1	-1.375	-1.667	0.3	-1.25	2.75	0	-0.75	-0.5	4	-1	1	-0.25	-5	-3	1.333	-1.75	-3	2.25	0	-1.5	1	-2.5	-1.25	1	-2.5	0.333	-0.5	0.5	1.5	-5.5	1.75	2.25	3	-5	-2	-3.5	0.5	-0.75	-2.5	1.125	-2.25	0	-1.5	3	3.5	1.5	2	4	3	0.5	4	-0.5	-2	-3.5	3.5	-1.75	-1.5	-5.5	0.5	1.5	-5.5	2.5	0.75	0	0.5	0.5	1.5	-3	2	-1.5	0.667	-1	0	1.25	1	1	-1	0	0	-1	0.5	2.5	1.5	1.5	-5	0.75	0.25	2.125	-3.75	-2.5	0.5

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
LFM_mannen	98	612.762	6.253	0.903	0.675
Residuals	58	401.508	6.923

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
LFM_mannen & 98 & 612.762 & 6.253 & 0.903 & 0.675 \tabularnewline
Residuals & 58 & 401.508 & 6.923 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267391&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]LFM_mannen[/C][C]98[/C][C]612.762[/C][C]6.253[/C][C]0.903[/C][C]0.675[/C][/ROW]
[ROW][C]Residuals[/C][C]58[/C][C]401.508[/C][C]6.923[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267391&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267391&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
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
LFM_mannen	98	612.762	6.253	0.903	0.675
Residuals	58	401.508	6.923

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = 1 ; par3 = TRUE ;

Parameters (R input):

par1 = 2 ; 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){
'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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code