CS计算机代考程序代写 ## —-echo=FALSE———————————————————-

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set.seed(2339)

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x <- c(1612, 1352, 1256, 922, 1560, 1456, 2324) y <- c(1082, 1300, 1092, 1040, 910 , 1248, 1092, 1040, 1092, 1288) ## ------------------------------------------------------------------------ t.test(x, y, var.equal = TRUE) ## ------------------------------------------------------------------------ var.test(x, y) ## ------------------------------------------------------------------------ t.test(x, y) ## ----fig.width=6, fig.height=4------------------------------------------- par(mfrow = c(1, 2)) qqnorm(x, main = "X", col = 4) qqline(x, lty = 2) qqnorm(y, main = "Y", col = 4) qqline(y, lty = 2) ## ------------------------------------------------------------------------ # Wilcoxon test with normal approximation wilcox.test(x, y, exact = FALSE) ## ----results='hide'------------------------------------------------------ y2 <- y y2[5] <- 470 wilcox.test(x, y2, exact = FALSE) ## ------------------------------------------------------------------------ butterfat <- read.table("butterfat.txt")[, 1] x.bar <- mean(butterfat) s <- sd(butterfat) ## ------------------------------------------------------------------------ b <- c(0, seq(374, 624, 50), 1000) # class boundaries O <- table(cut(butterfat, breaks = b)) # observed counts O ## ------------------------------------------------------------------------ prob <- rep(0, 7) for (k in 1:7) prob[k] <- pnorm(b[k + 1], x.bar, s) - pnorm(b[k], x.bar, s) E <- prob * length(butterfat) # expected frequencies ## ------------------------------------------------------------------------ C <- sum((O - E)^2 / E) # chi-squared statistic d1 <- length(O) # number of classes qchisq(0.95, d1 - 3) # critical value 1 - pchisq(C, d1 - 3) # p-value cbind(O, E) ## ------------------------------------------------------------------------ chisq.test(O, p = prob) ## ------------------------------------------------------------------------ 1 - pchisq(1.0144, d1 - 3) ## ------------------------------------------------------------------------ X.raw <- c(171, 93, 82, 62, 54, 11, 31, 55, 43, 11, 27, 57) X <- matrix(X.raw, nrow = 4, byrow = TRUE) test <- chisq.test(X) test ## ------------------------------------------------------------------------ test$expected ## ------------------------------------------------------------------------ E.1 <- sum(X[, 1]) * sum(X[1, ]) / sum(X) E.1 O.1 <- 171 (O.1 - E.1)^2 / E.1