ETF2100/5910 Introductory Econometrics
Assignment 1, Semester 2, 2023
IMPORTANT NOTES:
• Type your answers using Microsoft Word or write your answers CLEARLY. You must submit
a PDF file to Moodle. Other file formats are not accepted. Name the file as follows: student
ID Name.pdf. Also, on the title page, please make sure you provide the student ID and name
correctly.
• Please save and submit your R script as well.
• Notation used in the assignment needs to be typed correctly and properly. Incorrect (or incon-
sistent) notations are treated as wrong answers.
• When doing calculation, keep at least 4 decimal in each step for precision. For final answer, 3
decimal point is sufficient, unless specified otherwise in the question.
• In this assignment, when you need to use t critical value, if the question does not specify, you
can either find it using R or use the statistical table. If the question specifies, use that method.
• This assignment is worth 10% of the unit’s total mark and is an individual assignment.
• Total marks for this assignment is 20.
• Marks will be deducted for late submission on the following basis: 2 marks off for each day
late, up to a maximum of 3 days. Assignments more than 3 days late will not be marked.
Question 1 (20 marks)
You will use the data file gamesale.csv to answer this question. It is a dataset on video games and
is available on Moodle in csv format. The variables were measured in December 2016 and are as
follows:
• name: Name of the video game
• sales: Total sales in the world (in thousands of units)
• score: Aggregate critic score compiled by Metacritic staff (on a 0−100 scale)
We are interested in the relationship between video games’ sales and critic score.
(a) Generate the descriptive statistics for sales and score and report them in a table. (1 Mark)
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(b) Estimate the following linear regression model by least squares. Report the result in full (i.e.,
the fitted model, including s.e. and R-squared) and include your regression result from R in
your answer. (3 marks)
salesi = β1 + β2scorei + ei (1)
(c) Interpret the estimated slope coefficient. Be careful about the unit of sales in your interpreta-
tion. (2 marks)
(d) Interpret the estimate of the intercept. Does it make sense? Comment. (2 marks)
(e) Interpret the R2 you found in part (b). (1 Marks)
(f) Predict total sales when critic score is 50. (2 marks)
(g) What level of critic score predicts sales of exactly 700,000 units? (2 marks)
(h) Test at the 5% level of significance the null hypothesis that “one unit increase in critic score is
associated with an increase in sales of 25,000 units,” using a two-tailed test. Be sure to write
down your null and alternative hypotheses and show all the steps used to conduct your test
using the test statistics approach. Use R to find the exact t-critical value. (5 marks)
(i) Construct a 90% confidence interval for β2. Interpret the confidence interval. (2 marks)
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