ECN 627 Econometrics I
Section 01/02/03/04/06/06
Fall 2021
Programming Assignment
Due Date: Nov 23, 2021
Instructions:
Please answer all questions using R-studio and paste the co
esponding outputs to this word file
for each question. Outputs can be found at the Console window located at the left bottom of R-
studio interface. You may either directly copy and paste the outputs or take screenshots of
them and paste the pictures. When pasting the outputs, please make sure you have included
the commands and ONLY the commands that produce these outputs.
Upload the filled word file to D2L – Assessments – Programming Assignment.
Here are two sample questions and their solutions:
Sample Question 1: How much is the natural logarithm of 10?
Solution 1 (screenshots):
Output:
Solution 2 (copy and paste):
Output:
log(10)
[1] XXXXXXXXXX
Sample Question 2: Clear the memory.
Solution 1 (screenshots):
Output:
Solution 2 (copy and paste):
Output:
rm(list = ls())
Note that in both outputs, we have lines staring with “>” (i.e. “>log(10)” and “
m(list=ls())”).
Such lines co
espond to your R codes that generate the results. Please make sure such
commands are included in your answer for each question. Some questions may need multiple
lines of commands. Do not include unnecessary lines.
Grading Policy: Each question from 1 to 12 is worth 2 marks. You get 1 mark for co
ect
commands and 1 mark for co
ect results. Question 13 is worth 6 marks. You get 3 marks fo
co
ect codes and 3 marks for co
ect graph. The total is 30 marks. The teaching assistant, Hari,
will grade the programming assignment and determine how to award partial credits.
Here is the assignment question:
Background: We want to predict the quality of red wine based on physicochemical tests. We
obtain a dataset, “winequality-red.csv”, with the following variables.
1 - fixed acidity
2 - volatile acidity
3 - citric acid
4 - residual suga
5 - chlorides
6 - free sulfur dioxide
7 - total sulfur dioxide
8 - density
9 - pH
10 - sulphates
11 - alcohol
Output variable (based on sensory data):
12 - quality (score between 0 and 10)
Please download the dataset and address the following questions.
Question 1: Clear memory, set the directory as the folder where you save the dataset
“winequality-red.csv”, and check if the directory is co
ectly specified.
Output:
Question 2: Load dataset using the “read.csv” command.
Output:
Question 3: Calculate the mean of variable “quality”.
Output:
Question 4: Calculate the variance of variable “quality”.
Output:
Question 5: Generate a new variable “log_quality”, as the natural logarithm of (“quality” +
XXXXXXXXXX).
Output:
Question 6: Regress “log_quality” on “alcohol” and summarize the regression results.
Output:
Question 7: Regress “log_quality” on “alcohol”, “fixed acidity”, “volatile acidity” and “residual
sugar”.
Output:
Question 8: List all the coefficients of the second regression.
Output:
Question 9: Display the OLS estimate of the coefficient of “alcohol” in the second regression.
Output:
Question 10: Display the standard e
or of the OLS estimate of the coefficient of “alcohol” in
the second regression.
Output:
Question 11: Compute and display the value of the t-statistic of
H0: the coefficient “alcohol” in the second regression is 0.05
H1: the coefficient “alcohol” in the second regression is not 0.05
Output:
Question 12: Compute and display the p-value of the hypothesis testing in question 12.
Output:
Question 13: Plot the “residual sugar” against “citric acid” and add a regression line of “residual
sugar” on “citric acid” (residual sugar is the dependent variable, citric acid is the regressor). Put
“residual sugar” at the vertical axis and the “citric acid” at the horizontal axis. In the output area
elow, you need to display both the results and the graph.
Output: