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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 computationTue, 29 Nov 2011 09:48:32 -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/29/t132257812618gymbajceg3hth.htm/, Retrieved Thu, 28 Mar 2024 20:13:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148451, Retrieved Thu, 28 Mar 2024 20:13:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79
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)] [] [2011-11-24 12:30:07] [483074838c7eb9e0ff7f7d3e3c3f8586]
-   PD              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-29 14:48:32] [7cb3389c165bc116919f8c93cbf97eb6] [Current]
-   P                 [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-29 14:49:34] [483074838c7eb9e0ff7f7d3e3c3f8586]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-29 15:24:08] [483074838c7eb9e0ff7f7d3e3c3f8586]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2011-11-29 15:22:16] [483074838c7eb9e0ff7f7d3e3c3f8586]
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Dataseries X:
80	2	'low'	1	44	88
11	1	'low'	1	39	79
66	2	'Medium'	1	34	90
145	2	'Medium'	1	56	98
126	2	'low'	1	39	80
160	3	'low'	1	51	96
91	3	'Medium'	1	48	85
29	1	'Medium'	1	52	94
6	1	'low'	1	44	68
78	2	'low'	1	52	91
70	2	'low'	1	55	70
110	3	'low'	1	39	112
43	1	'Medium'	1	42	80
46	2	'Medium'	1	30	94
131	3	'Medium'	1	39	86
155	2	'Medium'	1	48	87
55	3	'low'	1	46	81
146	3	'low'	1	59	96
21	2	'low'	1	52	90
120	2	'low'	1	46	77
42	2	'low'	1	49	95
16	1	'Medium'	1	41	70
37	3	'Medium'	1	50	88
75	2	'Medium'	1	54	92
2	1	'Medium'	1	36	88
41	1	'Medium'	1	36	94
92	2	'Medium'	1	44	75
124	2	'Medium'	1	30	78
47	2	'Medium'	1	52	88
141	3	'High'	1	39	91
121	3	'High'	1	43	88
54	3	'low'	2	57	102
23	1	'low'	2	44	85
5	3	'low'	2	32	73
93	3	'low'	2	41	77
101	2	'low'	2	55	95
122	2	'low'	2	44	75
69	2	'low'	2	55	86
28	3	'Medium'	2	44	79
81	3	'Medium'	2	46	97
100	1	'Medium'	2	54	107
7	2	'Medium'	2	39	80
140	3	'Medium'	2	43	86
148	2	'Medium'	2	57	100
17	3	'Medium'	2	55	86
31	3	'Medium'	2	44	86
30	2	'Medium'	2	54	97
20	2	'Medium'	2	39	79
13	3	'Medium'	2	52	92
108	3	'Medium'	2	44	95
63	2	'Medium'	2	62	95
33	2	'Medium'	2	37	87
53	3	'High'	2	43	109
154	3	'High'	2	41	88
119	3	'High'	2	58	111
18	3	'low'	2	41	87
158	1	'low'	2	56	102
138	2	'low'	2	48	90
40	1	'low'	2	31	75
133	2	'low'	2	43	90
109	2	'low'	2	57	97
22	1	'low'	2	46	95
136	3	'low'	2	43	86
147	3	'low'	2	46	95
82	1	'Medium'	2	59	90
149	3	'Medium'	2	50	95
58	2	'Medium'	2	48	97
104	3	'Medium'	2	44	101
114	1	'Medium'	2	50	94
25	3	'Medium'	2	41	90
65	3	'Medium'	2	46	95
156	3	'Medium'	2	59	100
45	3	'Medium'	2	41	68
127	3	'Medium'	2	37	87
88	1	'Medium'	2	59	103
103	3	'Medium'	2	59	115
3	3	'Medium'	2	56	94
51	1	'Medium'	2	66	98
135	3	'Medium'	2	55	94
79	3	'Medium'	2	32	68
15	3	'Medium'	2	50	96
99	3	'Medium'	2	46	106
87	2	'Medium'	2	56	100
89	3	'Medium'	2	57	94
8	3	'Medium'	2	34	86
62	2	'Medium'	2	58	95
44	1	'Medium'	2	37	95
77	2	'High'	2	46	102
115	3	'High'	2	39	103
4	3	'High'	2	48	90
67	3	'High'	2	66	107
48	1	'low'	3	30	84
56	3	'low'	3	54	97
111	3	'low'	3	60	97
137	3	'low'	3	60	86
14	3	'low'	3	37	72
52	2	'low'	3	48	78
105	1	'low'	3	54	85
9	3	'low'	3	41	86
90	1	'Medium'	3	52	97
57	2	'Medium'	3	48	75
76	2	'Medium'	3	55	97
38	1	'Medium'	3	52	82
157	3	'Medium'	3	60	98
34	3	'Medium'	3	52	98
123	3	'Medium'	3	34	92
132	3	'Medium'	3	36	85
27	1	'Medium'	3	50	84
84	3	'Medium'	3	46	94
106	3	'Medium'	3	52	90
102	2	'Medium'	3	54	107
39	2	'High'	3	55	111
12	1	'High'	3	62	96
134	1	'High'	3	50	101
19	3	'High'	3	56	88
86	1	'High'	3	66	109
32	2	'High'	3	52	111
26	1	'High'	3	50	115
10	2	'High'	3	50	91
35	1	'Medium'	3	50	87
68	3	'Medium'	3	52	92
83	3	'Medium'	3	46	101
125	2	'Medium'	3	50	106
85	1	'High'	3	54	101
107	3	'High'	3	66	115
153	1	'High'	3	59	115




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148451&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148451&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148451&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'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
MC30VRB ~ MWARM30
means44.8063.366.422

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MWARM30 \tabularnewline
means & 44.806 & 3.36 & 6.422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148451&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]44.806[/C][C]3.36[/C][C]6.422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148451&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148451&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 ~ MWARM30
means44.8063.366.422







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM302678.085339.0434.940.009
Residuals1238441.34368.629

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 2 & 678.085 & 339.043 & 4.94 & 0.009 \tabularnewline
Residuals & 123 & 8441.343 & 68.629 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148451&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]MWARM30[/C][C]2[/C][C]678.085[/C][C]339.043[/C][C]4.94[/C][C]0.009[/C][/ROW]
[ROW][C]Residuals[/C][C]123[/C][C]8441.343[/C][C]68.629[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148451&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148451&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)
MWARM302678.085339.0434.940.009
Residuals1238441.34368.629







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-13.36-0.9877.7070.163
3-16.4221.57511.2690.006
3-23.062-1.1187.2420.195

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 3.36 & -0.987 & 7.707 & 0.163 \tabularnewline
3-1 & 6.422 & 1.575 & 11.269 & 0.006 \tabularnewline
3-2 & 3.062 & -1.118 & 7.242 & 0.195 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148451&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]3.36[/C][C]-0.987[/C][C]7.707[/C][C]0.163[/C][/ROW]
[ROW][C]3-1[/C][C]6.422[/C][C]1.575[/C][C]11.269[/C][C]0.006[/C][/ROW]
[ROW][C]3-2[/C][C]3.062[/C][C]-1.118[/C][C]7.242[/C][C]0.195[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148451&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148451&T=3

As an alternative you can also use a QR Code:  

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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-13.36-0.9877.7070.163
3-16.4221.57511.2690.006
3-23.062-1.1187.2420.195







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group210.371
123

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1 & 0.371 \tabularnewline
  & 123 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148451&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]1[/C][C]0.371[/C][/ROW]
[ROW][C] [/C][C]123[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148451&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148451&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)
Group210.371
123



Parameters (Session):
par1 = 5 ; par2 = 4 ; par3 = TRUE ;
Parameters (R input):
par1 = 5 ; par2 = 4 ; 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')