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*The author of this computation has been verified*

R Software Module: Ian.Holliday/rwasp_One Factor ANOVA.wasp (opens new window with default values)

Title produced by software: Chi Square Measure of Association- Free Statistics Software (Calculator)

Date of computation: Tue, 15 Dec 2009 05:09:39 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/15/t12608792161hvlodro26ebvz4.htm/, Retrieved Tue, 15 Dec 2009 13:13:39 +0100

BibTeX entries for LaTeX users:

@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Dec/15/t12608792161hvlodro26ebvz4.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

2 36 2 56 3 48 1 32 1 44 2 39 2 34 1 41 3 50 1 39 3 62 2 52 1 37 2 50 2 41 2 55 1 41 3 56 2 39 1 52 1 46 1 44 2 41 3 50 2 50 1 44 2 52 2 54 2 44 3 52 2 37 2 52 2 50 1 36 2 50 2 52 3 55 1 31 2 36 1 49 2 42 2 37 2 41 2 30 2 52 1 30 2 44 2 66 1 48 3 43 1 57 1 46 1 54 2 48 2 48 2 1 62 1 58 2 58 2 62 2 46 2 34 3 66 2 52 1 55 1 55 2 57 2 56 2 55 3 56 2 54 2 55 3 46 1 52 2 32 1 44 2 46 2 59 2 46 2 46 3 54 3 66 2 56 2 59 2 57 2 52 2 48 2 44 1 41 1 50 1 48 3 48 1 59 2 46 2 54 1 55 2 54 2 59 2 44 1 54 2 52 3 66 2 44 1 57 1 39 1 60 1 45 2 41 2 50 3 39 2 43 2 48 2 37 3 58 1 46 3 43 1 44 2 34 2 30 2 50 1 39 2 37 1 55 2 39 2 36 1 43 3 50 2 55 1 43 1 60 1 48 1 30 2 43 3 39 2 52 2 39 1 39 2 56 1 59 1 46 2 57 2 50 2 54 2 50 3 60 3 59 3 41 2 48 2 59 2 60 1 56 1 51

Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

ANOVA Model
RespVar ~ AgeGroup
means	47.667	2.699	1.133	-46.167	-46.667	-46.667	-45.667	-46	-46	-46	-46.067	-45.667	-44.667	-46.267	-46.667	-45.667	-46.667	-45.333	-45.667	-46.167	-45.167	-45.167	-46.667	-44.667	-45.667

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
AgeGroup	24	79248.241	3302.01	47.284	0
Residuals	127	8868.858	69.834

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
2-1	2.699	-4.468	9.866	0.999
3-1	1.133	-8.752	11.019	1
30-1	-46.167	-68.996	-23.337	0
31-1	-46.667	-78.444	-14.89	0
32-1	-46.667	-78.444	-14.89	0
34-1	-45.667	-77.444	-13.89	0
36-1	-46	-64.929	-27.071	0
37-1	-46	-64.929	-27.071	0
39-1	-46	-64.929	-27.071	0
41-1	-46.067	-61.167	-30.967	0
42-1	-45.667	-77.444	-13.89	0
43-1	-44.667	-76.444	-12.89	0
44-1	-46.267	-61.367	-31.167	0
46-1	-46.667	-69.496	-23.837	0
48-1	-45.667	-62.306	-29.027	0
49-1	-46.667	-78.444	-14.89	0
50-1	-45.333	-59.313	-31.353	0
52-1	-45.667	-58.788	-32.545	0
54-1	-46.167	-68.996	-23.337	0
55-1	-45.167	-67.996	-22.337	0
56-1	-45.167	-67.996	-22.337	0
57-1	-46.667	-78.444	-14.89	0
62-1	-44.667	-76.444	-12.89	0
66-1	-45.667	-77.444	-13.89	0
3-2	-1.565	-10.727	7.596	1
30-2	-48.865	-71.391	-26.34	0
31-2	-49.365	-80.925	-17.806	0
32-2	-49.365	-80.925	-17.806	0
34-2	-48.365	-79.925	-16.806	0
36-2	-48.699	-67.26	-30.137	0
37-2	-48.699	-67.26	-30.137	0
39-2	-48.699	-67.26	-30.137	0
41-2	-48.765	-63.402	-34.129	0
42-2	-48.365	-79.925	-16.806	0
43-2	-47.365	-78.925	-15.806	0
44-2	-48.965	-63.602	-34.329	0
46-2	-49.365	-71.891	-26.84	0
48-2	-48.365	-64.585	-32.145	0
49-2	-49.365	-80.925	-17.806	0
50-2	-48.032	-61.51	-34.554	0
52-2	-48.365	-60.951	-35.78	0
54-2	-48.865	-71.391	-26.34	0
55-2	-47.865	-70.391	-25.34	0
56-2	-47.865	-70.391	-25.34	0
57-2	-49.365	-80.925	-17.806	0
62-2	-47.365	-78.925	-15.806	0
66-2	-48.365	-79.925	-16.806	0
30-3	-47.3	-70.832	-23.768	0
31-3	-47.8	-80.085	-15.515	0
32-3	-47.8	-80.085	-15.515	0
34-3	-46.8	-79.085	-14.515	0
36-3	-47.133	-66.904	-27.363	0
37-3	-47.133	-66.904	-27.363	0
39-3	-47.133	-66.904	-27.363	0
41-3	-47.2	-63.343	-31.057	0
42-3	-46.8	-79.085	-14.515	0
43-3	-45.8	-78.085	-13.515	0
44-3	-47.4	-63.543	-31.257	0
46-3	-47.8	-71.332	-24.268	0
48-3	-46.8	-64.391	-29.209	0
49-3	-47.8	-80.085	-15.515	0
50-3	-46.467	-61.567	-31.367	0
52-3	-46.8	-61.109	-32.491	0
54-3	-47.3	-70.832	-23.768	0
55-3	-46.3	-69.832	-22.768	0
56-3	-46.3	-69.832	-22.768	0
57-3	-47.8	-80.085	-15.515	0
62-3	-45.8	-78.085	-13.515	0
66-3	-46.8	-79.085	-14.515	0
31-30	-0.5	-38.786	37.786	1
32-30	-0.5	-38.786	37.786	1
34-30	0.5	-37.786	38.786	1
36-30	0.167	-28.37	28.703	1
37-30	0.167	-28.37	28.703	1
39-30	0.167	-28.37	28.703	1
41-30	0.1	-26.054	26.254	1
42-30	0.5	-37.786	38.786	1
43-30	1.5	-36.786	39.786	1
44-30	-0.1	-26.254	26.054	1
46-30	-0.5	-31.76	30.76	1
48-30	0.5	-26.572	27.572	1
49-30	-0.5	-38.786	37.786	1
50-30	0.833	-24.69	26.357	1
52-30	0.5	-24.564	25.564	1
54-30	0	-31.26	31.26	1
55-30	1	-30.26	32.26	1
56-30	1	-30.26	32.26	1
57-30	-0.5	-38.786	37.786	1
62-30	1.5	-36.786	39.786	1
66-30	0.5	-37.786	38.786	1
32-31	0	-44.209	44.209	1
34-31	1	-43.209	45.209	1
36-31	0.667	-35.429	36.763	1
37-31	0.667	-35.429	36.763	1
39-31	0.667	-35.429	36.763	1
41-31	0.6	-33.644	34.844	1
42-31	1	-43.209	45.209	1
43-31	2	-42.209	46.209	1
44-31	0.4	-33.844	34.644	1
46-31	0	-38.286	38.286	1
48-31	1	-33.95	35.95	1
49-31	0	-44.209	44.209	1
50-31	1.333	-32.432	35.098	1
52-31	1	-32.419	34.419	1
54-31	0.5	-37.786	38.786	1
55-31	1.5	-36.786	39.786	1
56-31	1.5	-36.786	39.786	1
57-31	0	-44.209	44.209	1
62-31	2	-42.209	46.209	1
66-31	1	-43.209	45.209	1
34-32	1	-43.209	45.209	1
36-32	0.667	-35.429	36.763	1
37-32	0.667	-35.429	36.763	1
39-32	0.667	-35.429	36.763	1
41-32	0.6	-33.644	34.844	1
42-32	1	-43.209	45.209	1
43-32	2	-42.209	46.209	1
44-32	0.4	-33.844	34.644	1
46-32	0	-38.286	38.286	1
48-32	1	-33.95	35.95	1
49-32	0	-44.209	44.209	1
50-32	1.333	-32.432	35.098	1
52-32	1	-32.419	34.419	1
54-32	0.5	-37.786	38.786	1
55-32	1.5	-36.786	39.786	1
56-32	1.5	-36.786	39.786	1
57-32	0	-44.209	44.209	1
62-32	2	-42.209	46.209	1
66-32	1	-43.209	45.209	1
36-34	-0.333	-36.429	35.763	1
37-34	-0.333	-36.429	35.763	1
39-34	-0.333	-36.429	35.763	1
41-34	-0.4	-34.644	33.844	1
42-34	0	-44.209	44.209	1
43-34	1	-43.209	45.209	1
44-34	-0.6	-34.844	33.644	1
46-34	-1	-39.286	37.286	1
48-34	0	-34.95	34.95	1
49-34	-1	-45.209	43.209	1
50-34	0.333	-33.432	34.098	1
52-34	0	-33.419	33.419	1
54-34	-0.5	-38.786	37.786	1
55-34	0.5	-37.786	38.786	1
56-34	0.5	-37.786	38.786	1
57-34	-1	-45.209	43.209	1
62-34	1	-43.209	45.209	1
66-34	0	-44.209	44.209	1
37-36	0	-25.524	25.524	1
39-36	0	-25.524	25.524	1
41-36	-0.067	-22.896	22.763	1
42-36	0.333	-35.763	36.429	1
43-36	1.333	-34.763	37.429	1
44-36	-0.267	-23.096	22.563	1
46-36	-0.667	-29.203	27.87	1
48-36	0.333	-23.542	24.209	1
49-36	-0.667	-36.763	35.429	1
50-36	0.667	-21.438	22.771	1
52-36	0.333	-21.238	21.905	1
54-36	-0.167	-28.703	28.37	1
55-36	0.833	-27.703	29.37	1
56-36	0.833	-27.703	29.37	1
57-36	-0.667	-36.763	35.429	1
62-36	1.333	-34.763	37.429	1
66-36	0.333	-35.763	36.429	1
39-37	0	-25.524	25.524	1
41-37	-0.067	-22.896	22.763	1
42-37	0.333	-35.763	36.429	1
43-37	1.333	-34.763	37.429	1
44-37	-0.267	-23.096	22.563	1
46-37	-0.667	-29.203	27.87	1
48-37	0.333	-23.542	24.209	1
49-37	-0.667	-36.763	35.429	1
50-37	0.667	-21.438	22.771	1
52-37	0.333	-21.238	21.905	1
54-37	-0.167	-28.703	28.37	1
55-37	0.833	-27.703	29.37	1
56-37	0.833	-27.703	29.37	1
57-37	-0.667	-36.763	35.429	1
62-37	1.333	-34.763	37.429	1
66-37	0.333	-35.763	36.429	1
41-39	-0.067	-22.896	22.763	1
42-39	0.333	-35.763	36.429	1
43-39	1.333	-34.763	37.429	1
44-39	-0.267	-23.096	22.563	1
46-39	-0.667	-29.203	27.87	1
48-39	0.333	-23.542	24.209	1
49-39	-0.667	-36.763	35.429	1
50-39	0.667	-21.438	22.771	1
52-39	0.333	-21.238	21.905	1
54-39	-0.167	-28.703	28.37	1
55-39	0.833	-27.703	29.37	1
56-39	0.833	-27.703	29.37	1
57-39	-0.667	-36.763	35.429	1
62-39	1.333	-34.763	37.429	1
66-39	0.333	-35.763	36.429	1
42-41	0.4	-33.844	34.644	1
43-41	1.4	-32.844	35.644	1
44-41	-0.2	-19.971	19.571	1
46-41	-0.6	-26.754	25.554	1
48-41	0.4	-20.57	21.37	1
49-41	-0.6	-34.844	33.644	1
50-41	0.733	-18.196	19.662	1
52-41	0.4	-17.904	18.704	1
54-41	-0.1	-26.254	26.054	1
55-41	0.9	-25.254	27.054	1
56-41	0.9	-25.254	27.054	1
57-41	-0.6	-34.844	33.644	1
62-41	1.4	-32.844	35.644	1
66-41	0.4	-33.844	34.644	1
43-42	1	-43.209	45.209	1
44-42	-0.6	-34.844	33.644	1
46-42	-1	-39.286	37.286	1
48-42	0	-34.95	34.95	1
49-42	-1	-45.209	43.209	1
50-42	0.333	-33.432	34.098	1
52-42	0	-33.419	33.419	1
54-42	-0.5	-38.786	37.786	1
55-42	0.5	-37.786	38.786	1
56-42	0.5	-37.786	38.786	1
57-42	-1	-45.209	43.209	1
62-42	1	-43.209	45.209	1
66-42	0	-44.209	44.209	1
44-43	-1.6	-35.844	32.644	1
46-43	-2	-40.286	36.286	1
48-43	-1	-35.95	33.95	1
49-43	-2	-46.209	42.209	1
50-43	-0.667	-34.432	33.098	1
52-43	-1	-34.419	32.419	1
54-43	-1.5	-39.786	36.786	1
55-43	-0.5	-38.786	37.786	1
56-43	-0.5	-38.786	37.786	1
57-43	-2	-46.209	42.209	1
62-43	0	-44.209	44.209	1
66-43	-1	-45.209	43.209	1
46-44	-0.4	-26.554	25.754	1
48-44	0.6	-20.37	21.57	1
49-44	-0.4	-34.644	33.844	1
50-44	0.933	-17.996	19.862	1
52-44	0.6	-17.704	18.904	1
54-44	0.1	-26.054	26.254	1
55-44	1.1	-25.054	27.254	1
56-44	1.1	-25.054	27.254	1
57-44	-0.4	-34.644	33.844	1
62-44	1.6	-32.644	35.844	1
66-44	0.6	-33.644	34.844	1
48-46	1	-26.072	28.072	1
49-46	0	-38.286	38.286	1
50-46	1.333	-24.19	26.857	1
52-46	1	-24.064	26.064	1
54-46	0.5	-30.76	31.76	1
55-46	1.5	-29.76	32.76	1
56-46	1.5	-29.76	32.76	1
57-46	0	-38.286	38.286	1
62-46	2	-36.286	40.286	1
66-46	1	-37.286	39.286	1
49-48	-1	-35.95	33.95	1
50-48	0.333	-19.845	20.512	1
52-48	0	-19.593	19.593	1
54-48	-0.5	-27.572	26.572	1
55-48	0.5	-26.572	27.572	1
56-48	0.5	-26.572	27.572	1
57-48	-1	-35.95	33.95	1
62-48	1	-33.95	35.95	1
66-48	0	-34.95	34.95	1
50-49	1.333	-32.432	35.098	1
52-49	1	-32.419	34.419	1
54-49	0.5	-37.786	38.786	1
55-49	1.5	-36.786	39.786	1
56-49	1.5	-36.786	39.786	1
57-49	0	-44.209	44.209	1
62-49	2	-42.209	46.209	1
66-49	1	-43.209	45.209	1
52-50	-0.333	-17.725	17.058	1
54-50	-0.833	-26.357	24.69	1
55-50	0.167	-25.357	25.69	1
56-50	0.167	-25.357	25.69	1
57-50	-1.333	-35.098	32.432	1
62-50	0.667	-33.098	34.432	1
66-50	-0.333	-34.098	33.432	1
54-52	-0.5	-25.564	24.564	1
55-52	0.5	-24.564	25.564	1
56-52	0.5	-24.564	25.564	1
57-52	-1	-34.419	32.419	1
62-52	1	-32.419	34.419	1
66-52	0	-33.419	33.419	1
55-54	1	-30.26	32.26	1
56-54	1	-30.26	32.26	1
57-54	-0.5	-38.786	37.786	1
62-54	1.5	-36.786	39.786	1
66-54	0.5	-37.786	38.786	1
56-55	0	-31.26	31.26	1
57-55	-1.5	-39.786	36.786	1
62-55	0.5	-37.786	38.786	1
66-55	-0.5	-38.786	37.786	1
57-56	-1.5	-39.786	36.786	1
62-56	0.5	-37.786	38.786	1
66-56	-0.5	-38.786	37.786	1
62-57	2	-42.209	46.209	1
66-57	1	-43.209	45.209	1
66-62	-1	-45.209	43.209	1

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	24	2.64	0
	127

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/15/t12608792161hvlodro26ebvz4/3p4yc1260878976.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t12608792161hvlodro26ebvz4/3p4yc1260878976.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t12608792161hvlodro26ebvz4/4r20q1260878976.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/15/t12608792161hvlodro26ebvz4/4r20q1260878976.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 1 ; par2 = 2 ; 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()

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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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