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Data X:
1 255 2 280.2 3 299.9 4 339.2 5 374.2 6 393.5 7 389.2 8 381.7 9 375.2 10 369 11 357.4 12 352.1 1 346.5 2 342.9 3 340.3 4 328.3 5 322.9 6 314.3 7 308.9 8 294 9 285.6 10 281.2 11 280.3 12 278.8 1 274.5 2 270.4 3 263.4 4 259.9 5 258 6 262.7 7 284.7 8 311.3 9 322.1 10 327 11 331.3 12 333.3 1 321.4 2 327 3 320 4 314.7 5 316.7 6 314.4 7 321.3 8 318.2 9 307.2 10 301.3 11 287.5 12 277.7 1 274.4 2 258.8 3 253.3 4 251 5 248.4 6 249.5 7 246.1 8 244.5 9 243.6 10 244 11 240.8 12 249.8 1 248 2 259.4 3 260.5 4 260.8 5 261.3 6 259.5 7 256.6 8 257.9 9 256.5 10 254.2 11 253.3 12 253.8 1 255.5 2 257.1 3 257.3 4 253.2 5 252.8 6 252 7 250.7 8 252.2 9 250 10 251 11 253.4 12 251.2 1 255.6 2 261.1 3 258.9 4 259.9 5 261.2 6 264.7 7 267.1 8 266.4 9 267.7 10 268.6 11 267.5 12 268.5 1 268.5 2 270.5 3 270.9 4 270.1 5 269.3 6 269.8 7 270.1 8 264.9 9 263.7 10 264.8 11 263.7 12 255.9 1 276.2 2 360.1 3 380.5 4 373.7 5 369.8 6 366.6 7 359.3 8 345.8 9 326.2 10 324.5 11 328.1 12 327.5 1 324.4 2 316.5 3 310.9 4 301.5 5 291.7 6 290.4 7 287.4 8 277.7 9 281.6 10 288 11 276 12 272.9 1 283 2 283.3 3 276.8 4 284.5 5 282.7 6 281.2 7 287.4 8 283.1 9 284 10 285.5 11 289.2 12 292.5 1 296.4 2 305.2 3 303.9 4 311.5 5 316.3 6 316.7 7 322.5 8 317.1 9 309.8 10 303.8 11 290.3 12 293.7 1 291.7 2 296.5 3 289.1 4 288.5 5 293.8 6 297.7 7 305.4 8 302.7 9 302.5 10 303 11 294.5 12 294.1 1 294.5 2 297.1 3 289.4 4 292.4 5 287.9 6 286.6 7 280.5 8 272.4 9 269.2 10 270.6 11 267.3 12 262.5 1 266.8 2 268.8 3 263.1 4 261.2 5 266 6 262.5 7 265.2 8 261.3 9 253.7 10 249.2 11 239.1 12 236.4 1 235.2 2 245.2 3 246.2 4 247.7 5 251.4 6 253.3 7 254.8 8 250 9 249.3 10 241.5 11 243.3 12 248 1 253 2 252.9 3 251.5 4 251.6 5 253.5 6 259.8 7 334.1 8 448 9 445.8 10 445 11 448.2 12 438.2 1 439.8 2 423.4 3 410.8 4 408.4 5 406.7 6 405.9 7 402.7 8 405.1 9 399.6 10 386.5 11 381.4 12 375.2 1 357.7 2 359 3 355 4 352.7 5 344.4 6 343.8 7 338 8 339 9 333.3 10 334.4 11 328.3 12 330.7 1 330 2 331.6 3 351.2 4 389.4 5 410.9 6 442.8 7 462.8 8 466.9 9 461.7 10 439.2 11 430.3 12 416.1 1 402.5 2 397.3 3 403.3 4 395.9 5 387.8 6 378.6 7 377.1 8 370.4 9 362 10 350.3 11 348.2 12 344.6 1 343.5 2 342.8 3 347.6 4 346.6 5 349.5 6 342.1 7 342 8 342.8 9 339.3 10 348.2 11 333.7 12 334.7 1 354 2 367.7 3 363.3 4 358.4 5 353.1 6 343.1 7 344.6 8 344.4 9 333.9 10 331.7 11 324.3 12 321.2 1 322.4 2 321.7 3 320.5 4 312.8 5 309.7 6 315.6 7 309.7 8 304.6 9 302.5 10 301.5 11 298.8 12 291.3 1 293.6 2 294.6 3 285.9 4 297.6 5 301.1 6 293.8 7 297.7 8 292.9 9 292.1 10 287.2 11 288.2 12 283.8 1 299.9 2 292.4 3 293.3 4 300.8 5 293.7 6 293.1 7 294.4 8 292.1 9 291.9 10 282.5 11 277.9 12 287.5 1 289.2 2 285.6 3 293.2 4 290.8 5 283.1 6 275 7 287.8 8 287.8 9 287.4 10 284 11 277.8 12 277.6 1 304.9 2 294 3 300.9 4 324 5 332.9 6 341.6 7 333.4 8 348.2 9 344.7 10 344.7 11 329.3 12 323.5 1 323.2 2 317.4 3 330.1 4 329.2 5 334.9 6 315.8 7 315.4 8 319.6 9 317.3 10 313.8 11 315.8 12 311.3
Names of X columns:
month USA
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
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')
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