程序代写 ##########################################

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## Homework 3
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## Question 1.
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rm(list=ls())

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## Question 2
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rm(list=ls())
ex1 <- c(79, 92, 81, 80, 79, 80, 78, 88, 86, 88, 77, 93) ex2 <- c(80, 75, 67, 82, 76, 71, 78, 78, 80, 77, 78, 75) scores <- data.frame(Exam1 = ex1, Exam2 = ex2) t.test(??, ??, conf.level = ??, alternative = ??, paired = ??) # Hence reject the null hypothesis. ########################################## ## Question 3 ########################################## rm(list=ls()) head(mtcars) # The scatter plot makes clear that the relationship between gross horse power and # quarter-mile time (seconds) is both negative and (approximately) linear. plot(??, ??, pch = 19, xlab = "Gross Horse Power", ylab = "Quarter Mile Time (seconds)") reg_eq_mtcars <- lm(??, data = mtcars) ??(reg_eq_mtcars) ########################################## ## Question 4 ########################################## rm(list = ls()) #load the data and preprocess housing.df <- read.csv("./Data/BostonHousing.csv") head(housing.df) str(housing.df) summary(housing.df) #remove the categorical response variable CAT..MEDV housing.df <- housing.df[,-c(14)] # Fill in the corresponding predictors/independent variables reg <- lm(??, data = housing.df) # Fill in the corresponding predictors/independent variables # library(forecast) pred <- predict(reg, newdata = new) 程序代写 CS代考 加微信: powcoder QQ: 1823890830 Email: powcoder@163.com