Business Growth and Revenue Maximisation in a Car Dealership
Generation Automobiles Pte Ltd sells second hand cars. Cars are parked in lots for potential customers to view and test drive. Mr. Satya Nitin, the general manager, wants to sell more cars. The main objective is to maximise revenue by increasing the number of cars sold and/or the prices of transactions. To that end, Mr Nitin wants to know the following: What make (brand) of cars should they hold? What models of cars should they hold? What features should be built in as standard in these cars? What features should be added optionally? Which locations sell more cars and/or at higher prices? Mr. Nitin came across a study done by the Car Dealers Association (CDA) on sales of cars in year 2014. The sample had 1000 transactions randomly selected from car dealers in the country. The sample proportions for make, model and add-on feature are similar to those of the population. Mr. Nitin speculates that this study could help him to address the above concerns but he is not sure how to interpret this study. Mr. Nitin has engaged you as a consultant to help and has provided you an excel file with this random sample of 1000 transactions. The variables in the data are:
Question 1
Compare Price$ between City and Non-city stores. Use descriptive statistics to describe the data on Price$. Identify the measures of location and dispersion. Organise the appropriate output from your software into a relevant statistical and graphical presentation of the data. What are your preliminary observation/s? Please interpret them in detail. Hint: Summaries and presentations should help you decide subsequent analysis.
Question 2
(a) State 95% confidence intervals for the Price$ of City and Non- city stores. Interpret these confidence intervals. With these findings, can you advise Mr. Nitin if decisions on store location are important in achieving his objective? How would you advise him to stock his cars at these stores?
(b) List the key assumption(s) you have made in constructing this confidence interval. Discuss if this/these assumption(s) are reasonable?
(c) Select and explain what will be your follow-up actions, including statistical tests, if the key assumptions (s) were found to be violated.
Question 3
Choose appropriate hypothesis tests to determine if the Price$ is different with and without each of the three add-on features: Theatre, Leather and GPS-Video_Rec. You should include the following: (a) State the null and alternative hypotheses and explain how you develop these hypotheses.
(b) Present the output from your software for an appropriate hypothesis test with α = 0.05. List the test statistic you use for this test. Explain your decision criteria.
(c) Execute the hypothesis tests and conclude if Theatre, Leather and/or GPS-Video_Rec have an impact on Price$. If yes, what is the impact? What is your advice to Mr. Nitin based on these conclusions?
(d) Discuss the assumptions you have made in performing these hypothesis test? Are these assumptions reasonable for this case? Please provide explanation/s to substantiate your view.
Question 4
Highlight three (3) possible business or statistical concerns regarding the approach used above to determine whether the mean Price$ is significantly different, with respect to a number of factors.
If your group has a free hand on the project, starting from measurements, sampling, to analysis, what recommendations would you give for the problem in question? Keep your answer within 400 to 500 words (indicate your word count)
Question 5
In about 300 words (indicate your word count), provide an executive summary of your analysis and findings to Mr. Nitin with respect to the opportunities to maximise revenue.
Attachment:- data.xls