ETF2121 - ETF5912 Data Analysis in Business
Semester 1, 2024
ETF2121 students ONLY
Assignment 3
Due: Friday 24 May 2024 (Week 12), 11:55 PM
This is an individual assignment worth 15 marks. You can submit your assignment early if you wish. Unless otherwise specified, feel free to report any decimal places you like when presenting your answers. Please include EViews outputs in your answers. In this assessment, you must not use generative artificial intelligence (AI) to generate any materials or content in relation to the assessment task.
You are required to complete your answers in a Word document and then upload your completed file in PDF through Moodle submission. Your assignment can be either (i) entirely handwritten or (ii) entirely typed or (iii) a mixture of handwritten and typed answers. You may take photos of handwritten answers and paste them on a Word document. If you prefer not to use Microsoft Word, feel free to try using apps such as Camscanner or Microsoft Lens: PDF Scanner (available on iPhones and Android phones) to convert photos of your handwritten answers directly into PDF. This app can combine multiple pages into one PDF document.
Please save your Word document as PDF with its file name as your name and student ID.
Need an extension? Visit the following website for more information:
https://www.monash.edu/students/admin/assessments/extensions-special-consideration
Question 1. ETF2121 students ONLY [2 marks]
An insurance company is thinking about o§ering discounts on its life insurance policies to nonsmokers. As part of its analysis, it randomly selects 1600 men who are 60 years old and asks them if they smoke at least one packet of cigarettes per day and if they have ever su§ered from heart disease.
The table below shows that 301 of those in the smokers group su§ered from heart disease, while 120 of those in the non-smokers group su§ered from heart disease.
Su§er from heart disease
|
Group
|
Yes
|
No
|
Total
|
|
Smokers
|
301
|
699
|
1000
|
|
Non-smokers
|
120
|
480
|
600
|
Construct a 95% confidence interval for the di§erence of population proportions of men su§ering from heart disease for smokers versus non-smokers, and interpret.
Question 2. ETF2121 students ONLY [7 marks]
Please include EViews outputs in your answers, thank you.
This question will be marked out of 17 and this mark will be converted to a mark out of 7 marks. This question will explore the connection between a workerís earnings and their education and age.
The data set comprises a random sample of 500 full-time workers and is stored in the EViews workfile q2_earnings.wf1. It includes the following variables for the workers.
earn = monthly earnings in dollars
educ = years of education
age = age in years
Consider the following model
earni = β0 + β1 educi + β2 agei + "i :
(a) [2 marks] What signs do you think β1 and β2 will have? Explain.
(b) [1 mark] Use EViews to run a regression of earn on educ and age: Write down the sample regression line. Report the results to 4 decimal places.
(c) [0.5 marks] Jenny is a 30-year old female with 15 years of education. Predict Jennyís earnings using the sample regression line in part (b).
(d) [0.5 marks] Emma is a 30-year old female with 16 years of education. Predict Emmaís earnings using the sample regression line in part (b).
(e) [0.5 marks] Calculate the di§erence in predicted earnings between Emma and Jenny; ie.
Emmaís predicted earnings minus Jennyís predicted earnings.
(f) [0.5 marks] In part (b), what is the value of β(^)1 ?
(g) [2 marks] Compare your answers in parts (e) and (f). Are they the same? Explain why or why not?
(h) [1 mark] Using a = 0:05 and the p-value approach, test the following hypothesis, H0 : β 1 = 0 vs HA : β1 0:
(i) [2 marks] Test the overall utility of the model by using the critical value approach. Use a = 0:05:
Consider the following regression model:
earni = β0 + β1 educi + β2 agei + β3 agei(2) + "i :
(j) [1.5 marks] Use EViews to run a regression of earn on educ; age and age2 : Write down the sample regression line. What shape of curve (convex or concave) do the estimates represent between earn and age? Explain.
(k) [2 marks] Is there evidence that age has a nonlinear effect on earn? Do the six steps of the test. Use a = 0:05:
Consider the following regression model:
ln (earni ) = β0 + β1 educi + β2 agei + "i :
(l) [1.5 marks] Use EViews to run a regression of ln (earni ) on educ and age: Write down the sample regression line. Interpret the estimated coe¢ cient β(^)2 :
(m) [2 marks] In part (l), if educ increases from 12 to 13, can you determine how earn is expected to change, holding age constant? If not, explain why not; if yes, explain why and how.
Question 3. ETF2121 students ONLY [6 marks]
You are employed as an analyst in a consulting firm in Melbourne. Your consulting firm has a consulting contract with a major housing construction company. You have been asked by your manager to write a brief report that uses statistical techniques that you have learnt in lecture material from Week 1 to Week 9 (inclusive) to characterise the housing market in Melbourne.
The construction company wants to target its housing building plans. The company is interested in understanding how housing prices (the dependent variable) are affected by factors such as house size, number of bedrooms and whether the house o§ers anice view. In particular the company wants to know which of the two variables - size of house or number of bedrooms ñ is relatively more important in determining the price of a house, and why? The company is interested to know if the size of the house increases from 200-square-meter to 220-square-meter, how are housing prices expected to change. Also the difference in the price of a house that has a nice view compared to a house that does not have a nice view.
The construction company has given you a data set in an Excel file (q3_etf2121.xlsx ) that contains information about 88 randomly selected houses in Melbourne to undertake this assignment. The Excel file contains the following variables:
1. price is the house price in thousands of dollars
2. size is the size of house in square-meters
3. bdroom is the number of bedrooms
4. view = 1 if house has a nice view
= 0 otherwise
Please refer to Tutorial 1 (Week 2) Question B1 part (a) if you would like to revise on how to read the data in the Excel file into EViews.
Your brief report should contain all of the empirical results using the data provided. For ex- ample, your brief report could include simple/multiple regression models, hypothesis testing and interpretation of the empirical results.
The aim of this brief report is to allow students to undertake statistical analysis by using the techniques taught in lectures/seminars to investigate a real-world problem. This question is intentionally open ended and so there are not necessarily "right or wrong answers". The quality of your brief report counts. For example, if you wrote "So many people wear heavy coats during winter because they want to stay warm" would receive more marks than if you wrote "So many people wear heavy coats during winter because they are fashion- conscious". You are an analyst writing a brief report for your boss :) Of most importance is a correct justification/interpretation of your empirical results. You may use Excel functions to report some of the empirical results if you prefer. You can type your brief report, but feel free to handwrite some parts or handwrite all of your brief report.
Although your brief report does not have a firm word limit, we suggest that your brief report does not exceed 600 words, excluding tables and graphs.