Purpose of the

assessment (with ULO

Mapping)

This assignment aims at assessing students’ understanding of different qualitative and quantitative research methodologies and techniques. Other purposes are:

1. Explain how statistical techniques can solve business problems 2. Identify and evaluate valid statistical techniques in a given scenario to solve business problems

3. Explain and justify the results of a statistical analysis in the context of critical reasoning for a business problem solving

4. Apply statistical knowledge to summarize data graphically and statistically, either manually or via a computer package

5. Justify and interpret statistical/analytical scenarios that best fit business solution

Weight

40 % of the total assessments

Total Marks

40

Word limit

2500 words ± 500

Submission Guidelines

• All work must be submitted on Blackboard by the due date, along with the completed assignment cover page. The template of the assignment cover page is provided in the assessment folder.

• The assignment must be in MS Word format, with no spacing, 11-pt Calibri font and 2 cm margins on all four sides with appropriate section headings and page numbers. Excel files, PDF files and other Black Board unsupported files are given zero marks (This is with reference to the report of the assignment).

• However, the assignment should be supported with the relevant data sets, calculations and charts in excel.

• Reference sources must be cited in the text of the report and listed appropriately at the end in a numbered reference list using the Adapted Harvard Referencing style. A penalty is applied for incorrect referencing.

• Submitted work should be your original work, showing your genuine engagement in this unit. Evidence of your original group work (allocation of tasks, discussion, file exchanges, drafts, etc.) needs to be presented.

• Students need to read and understand the Holmes Academic Conduct and Integrity Policy before they start any assessment to ensure that their assignment is misconduct-free.

• Three (3) attempts of submission are allowed, and only the final submission will be graded.

• When you submit your assignment electronically, please save the file as ‘Group Assignment- your Group number.doc’. You are required to submit the assignment at Blackboard/Assessments/Group Assignment Information/Group Assignment and Submission Link.

• Always keep an electronic copy of your original file until you have received the final grade for the unit. Please ensure that you submit the correct file in the correct format that is readable on Blackboard.

Group Assignment Questions

Question 1 (10 marks)

Suppose that the average waiting time for a patient at a physician’s office is just over 29 minutes. To address the issue of long patients’, wait times, some physicians’ offices are using wait-tracking systems to notify patients of expected wait times. Patients can adjust their arrival times based on this information and spend less time in waiting rooms. The following data show wait times (in minutes) for a sample of patients at offices that do not have a wait-tracking system and wait times for a sample of patients at offices with such systems. The data are stored in HI6007 Group Assignment T1 2024 data file (sheet 1).

Without

Wait-Tracking System

With

Wait-Tracking System

30

25

72

8

12

16

24

20

46

9

32

28

26

12

12

10

35

7

15

14

a) Calculate the mean and median patient wait times for offices;

i. with a wait-tracking system?

ii. without a wait-tracking system?

(2 marks)

b) Calculate the variance and standard deviation of patient wait times for offices; i. with a wait-tracking system?

ii. without a wait-tracking system?

(2 marks)

c) Create a box plot for patient wait times for offices;

i. with a wait-tracking system and review the information from the box plot? ii. without a wait-tracking system and review the information from the box plot? (4 marks)

d) Do offices with a wait-tracking system have shorter patient wait times than offices without a wait-tracking system? Explain.

(2 marks)

Question 2 (10 marks)

Suppose a researcher has collected sample data on beer price (in $/per litre) and per capita beer quantity consumed (in litres) in Australia between 1975-2017. The data are stored in HI6007 Group Assignment T1 2024 data file (sheet 2).

Answer the following questions

a) Prepare a numerical summary output for the two variables; beer price and per capita beer quantity consumed and explain the key numerical descriptive measures.

(2 marks)

b) Based on the numerical descriptive measures, comment on the shape of the distribution of the two variables; beer price and per capita beer quantity consumed.

(2 marks)

c) Test the hypothesis that the population mean per capita beer consumption is less than 135 litres/year.

(2 marks)

d) If the researcher claims that the population mean per capita beer consumption is greater than 135 litres/year do you agree with that? Explain why.

(2 marks)

e) Based on part (c) and (d), what can you say about the population mean per capita beer consumption in Australia?

(2 marks)

Question 3 (20 marks)

Dixie Showtime Movie Theatres, Inc. owns and operates a chain of cinemas in several markets in the southern United States. The owners would like to estimate weekly gross revenue as a function of advertising expenditures. The data are stored in HI6007 Group Assignment T1 2024 data file (sheet 3). Using this data set and EXCEL, and no more than 1500 words in total, answer the following questions.

a) Using an appropriate numerical descriptive measure, comment on the strength and the direction of the linear relationship between weekly gross revenue and television advertising; and weekly gross revenue and newspaper advertising.

(2 marks)

b) Develop a simple linear regression model to estimate the relationship between weekly gross revenue and television advertising expenditure and Comment on the goodness of fit of the estimated model.

(2 marks)

c) Develop and estimate a multiple linear regression model to estimate the relationship between weekly gross revenue and television and newspaper

advertising expenditure. (2 marks)

d) What do the estimated regression coefficients in part (c) reveal about the relationship between weekly gross revenue and television and newspaper advertising expenditure? (2 marks)

e) Test the overall validity of the estimated multiple regression model in part (d) at the 5% level of significance.

(2 marks)

f) Test whether linear relationship exists between weekly gross revenue and individual independent variables in part (d) at the 5% level of significance.

(2 marks)

g) Will your conclusion in part (f) change if the level of significance changes to 1% level of significance?

(1 mark)

h) Compare the fitness of the multiple linear regression model with that of the simple linear regression model.

(2 mark)

i) Based on your answers to (a) to (h) above, write a research report (of maximum 300 words) for the head of research division of your company, summarizing your findings and highlighting the managerial implications of these results?