Description
Instructions: Students should submit their reports on Canvas. The report needs to clearly state what question is being solved, step-by-step walk-through solutions, and final answers clearly indicated. Please solve by hand where appropriate.
Please submit two files: (1) a R Markdown file (.Rmd extension) and (2) a PDF document generated using knitr for the .Rmd file submitted in (1) where appropriate. Please, use RStudio Cloud for your solutions.
Question 1 – 10pts
Question 2 – 10pts
Question 3 – 30pts
Question 4 – 30pts
Question 5 – 20pts
- For the regression model Yi=β0+εi, derive the least square estimation for β0?
- The dataset teengamb (see below for the instructions in r) concerns a study of teenage gambling in Britain. Make a numerical and graphical summary of the data, commenting on any features that you find interesting. Limit the output you present to a quantity that a busy reader would find sufficient to get a basic understanding of the data.
library(faraway) # download the library
data.help(“teengamb”) # see the description of the data
- Refer to the CDI data set. The number of active physicians in a CDI (Y) is
expected to be related to total population, number of hospital beds, and total personal income.
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- Regress the number of active physicians in turn on each of the three predictor variables. State the estimated regression functions.
- Plot the three estimated regression functions and data on separate graphs. Does a linear regression relation appear to provide a good fit for each of the three predictor variables?
- Calculate MSE for each of the three predictor variables. Which predictor variable leads to the smallest variability around the fitted regression line?
- Repeat question 3, by building the models on the development sample (a random sample of 70% of CDI data), and calculating MSE’s on the hold out sample (remainder 30% of the CDI data).
- The dataset teengamb concerns a study of teenage gambling in Britain.
- Regress the expenditure on gambling (Y) on income (X). State the estimated regression function. Compute the mean and median of the residuals.
- Which observation has the largest (positive) residual? Give the case number.