EXERCISE 2 ANOVA 2

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

Date of computation: Tue, 30 Nov 2010 13:15:21 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/30/t1291122846811quq5rw27vdzj.htm/, Retrieved Tue, 30 Nov 2010 14:14:07 +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/2010/Nov/30/t1291122846811quq5rw27vdzj.htm/}, year = {2010}, } @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 = {2010}, 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:

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44 80 34 80 56 80 59 80 50 80 50 80 48 81 46 81 59 81 54 81 44 81 50 81 43 81 39 82 42 82 52 82 41 83 46 83 57 83 43 83 52 83 57 83 59 83 56 83 41 84 50 84 50 84 41 84 48 84 48 84 37 84 55 85 44 85 30 85 44 85 54 85 55 85 59 85 48 85 59 85 37 85 39 85 48 85 36 86 56 86 54 86 52 86 66 86 55 86 60 86 52 87 36 87 32 87 34 87 36 87 56 87 50 88 39 88 52 89 44 89 46 89 44 89 41 89 56 90 54 90 50 91 52 91 55 91 62 92 52 92 57 92 34 92 30 92 39 92 34 93 37 93 52 93 58 93 48 93 46 93 46 93 52 93 50 93

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 'RServer@AstonUniversity' @ vre.aston.ac.uk ANOVA Model MC30VRB ~ MVRIQ2 means 48.833 0.31 -4.5 2.542 -3.833 -1.167 5.31 -7.833 -4.333 -3.433 6.167 3.5 -3.167 -1.833 ANOVA Statistics Df Sum Sq Mean Sq F value Pr(>F) MVRIQ2 13 1020.086 78.468 1.169 0.32 Residuals 69 4631.456 67.123 Tukey Honest Significant Difference Comparisons diff lwr upr p adj 81-80 0.31 -15.535 16.154 1 82-80 -4.5 -24.637 15.637 1 83-80 2.542 -12.839 17.922 1 84-80 -3.833 -19.677 12.011 1 85-80 -1.167 -15.406 13.073 1 86-80 5.31 -10.535 21.154 0.996 87-80 -7.833 -24.275 8.609 0.924 88-80 -4.333 -27.586 18.919 1 89-80 -3.433 -20.678 13.811 1 90-80 6.167 -17.086 29.419 1 91-80 3.5 -16.637 23.637 1 92-80 -3.167 -19.609 13.275 1 93-80 -1.833 -16.843 13.176 1 82-81 -4.81 -24.462 14.843 1 83-81 2.232 -12.507 16.971 1 84-81 -4.143 -19.365 11.08 1 85-81 -1.476 -15.02 12.068 1 86-81 5 -10.222 20.222 0.997 87-81 -8.143 -23.987 7.701 0.875 88-81 -4.643 -27.477 18.191 1 89-81 -3.743 -20.418 12.933 1 90-81 5.857 -16.977 28.691 1 91-81 3.19 -16.462 22.843 1 92-81 -3.476 -19.32 12.368 1 93-81 -2.143 -16.495 12.209 1 83-82 7.042 -12.238 26.322 0.991 84-82 0.667 -18.985 20.319 1 85-82 3.333 -15.05 21.716 1 86-82 9.81 -9.843 29.462 0.896 87-82 -3.333 -23.471 16.804 1 88-82 0.167 -25.831 26.164 1 89-82 1.067 -19.731 21.865 1 90-82 10.667 -15.331 36.664 0.975 91-82 8 -15.253 31.253 0.995 92-82 1.333 -18.804 21.471 1 93-82 2.667 -16.319 21.652 1 84-83 -6.375 -21.114 8.364 0.962 85-83 -3.708 -16.707 9.29 0.999 86-83 2.768 -11.971 17.507 1 87-83 -10.375 -25.755 5.005 0.529 88-83 -6.875 -29.389 15.639 0.998 89-83 -5.975 -22.21 10.26 0.99 90-83 3.625 -18.889 26.139 1 91-83 0.958 -18.322 20.238 1 92-83 -5.708 -21.089 9.672 0.99 93-83 -4.375 -18.213 9.463 0.998 85-84 2.667 -10.878 16.211 1 86-84 9.143 -6.08 24.365 0.707 87-84 -4 -19.844 11.844 1 88-84 -0.5 -23.334 22.334 1 89-84 0.4 -16.275 17.075 1 90-84 10 -12.834 32.834 0.959 91-84 7.333 -12.319 26.985 0.989 92-84 0.667 -15.177 16.511 1 93-84 2 -12.352 16.352 1 86-85 6.476 -7.068 20.02 0.922 87-85 -6.667 -20.906 7.573 0.932 88-85 -3.167 -24.918 18.584 1 89-85 -2.267 -17.426 12.892 1 90-85 7.333 -14.418 29.084 0.996 91-85 4.667 -13.716 23.05 1 92-85 -2 -16.239 12.239 1 93-85 -0.667 -13.225 11.891 1 87-86 -13.143 -28.987 2.701 0.21 88-86 -9.643 -32.477 13.191 0.969 89-86 -8.743 -25.418 7.933 0.858 90-86 0.857 -21.977 23.691 1 91-86 -1.81 -21.462 17.843 1 92-86 -8.476 -24.32 7.368 0.84 93-86 -7.143 -21.495 7.209 0.898 88-87 3.5 -19.753 26.753 1 89-87 4.4 -12.845 21.645 1 90-87 14 -9.253 37.253 0.703 91-87 11.333 -8.804 31.471 0.788 92-87 4.667 -11.775 21.109 0.999 93-87 6 -9.01 21.01 0.98 89-88 0.9 -22.927 24.727 1 90-88 10.5 -17.979 38.979 0.99 91-88 7.833 -18.164 33.831 0.999 92-88 1.167 -22.086 24.419 1 93-88 2.5 -19.763 24.763 1 90-89 9.6 -14.227 33.427 0.979 91-89 6.933 -13.865 27.731 0.996 92-89 0.267 -16.978 17.511 1 93-89 1.6 -14.285 17.485 1 91-90 -2.667 -28.664 23.331 1 92-90 -9.333 -32.586 13.919 0.979 93-90 -8 -30.263 14.263 0.992 92-91 -6.667 -26.804 13.471 0.996 93-91 -5.333 -24.319 13.652 0.999 93-92 1.333 -13.676 16.343 1 Levenes Test for Homogeneity of Variance Df F value Pr(>F) Group 13 1.19 0.305 69

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/30/t1291122846811quq5rw27vdzj/3g2dl1291122916.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/30/t1291122846811quq5rw27vdzj/3g2dl1291122916.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/30/t1291122846811quq5rw27vdzj/4g2dl1291122916.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/30/t1291122846811quq5rw27vdzj/4g2dl1291122916.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')

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Software written by Ed van Stee & Patrick Wessa

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