HI6007 Statistics for Business Decisions Assignment
Group Assessment
Cover Page
| Unit Details | Name | Statistics for Business Decisions |
| Code | HI6007 | |
| Year, Trimester | 2023 Trimester 1 |
| Assessment Details | Name | Group Assignment |
| Due Date and Week | Friday of Week 11 (02 June 2023) |
| Group Student Details | Student ID | First Name | Family Name | Work Contribution |
| Group Submission Declaration | Integrity Declaration | Student ID | Full Name | Submission Date |
| We have read and understand academic integrity policies and practices and our assessment does not violate these. | ||||
Instructions
| Academic Integrity Information | Holmes Institute is committed to ensuring and upholding academic integrity. All assessment must comply with academic integrity guidelines. Important academic integrity breaches include plagiarism, collusion, copying, impersonation, contract cheating, data fabrication and falsification. Please learn about academic integrity and consult your teachers with any questions. Violating academic integrity is serious and punishable by penalties that range from deduction of marks, failure of the assessment task or unit involved, suspension of course enrolment, or cancellation of course enrolment. |
| Format Instructions | Assessments must be in MS Word format with no spacing, 11-pt Calibri font and at least 2cm margins on all four sides with appropriate section headings and page numbers.
You must name your file with the Unit Code and Group Number (e.g. “HI6007 Group 4”). Check that you submit the correct document as special consideration is not granted if you make a mistake. Student IDs need to be indicated on the cover page. Non-contributing students do not receive marks. |
| Penalties | All work must be submitted on Blackboard by the due date and time along with a completed Assessment Cover Page. Late penalties apply.
Reference sources must be cited in the text of the report, and listed appropriately at the end in a reference list using Holmes Institute Adapted Harvard Referencing. Penalties are associated with incorrect citation and referencing. |
| Group Assignment Specifications
Purpose: Explain how statistical techniques can solve business problems Identify and evaluate valid statistical techniques in a given scenario to solve business problems Explain and justify the results of a statistical analysis in the context of critical reasoning for a business problem solving Apply statistical knowledge to summarize data graphically and statistically, either manually or via a computer package Justify and interpret statistical/analytical scenarios that best fit business solution Assignment Structure should be as the following: |
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| This is an applied assignment. Students have to show that they understand the principles and techniques taught in this course. Therefore, students are expected to show all the workings, and all problems must be completed in the format taught in class, the lecture notes or prescribed text book. Any problems not done in the prescribed format will not be marked, regardless of the ultimate correctness of the answer. (Note: The questions and the necessary data are provided under “Assignment and Due date” in the Blackboard.) |
| Instructions:
Your assignment must be submitted in WORD format only. When answering questions, wherever required, you should copy/cut and paste the Excel output (e.g., plots, regression output etc.) to show your working/output. Otherwise, you will not receive the allocated marks. Please note that you must attached your excel file with data, tables and outputs to support your work. Assignments without excel file will gets 10% penalty. You are required to keep an electronic copy of your submitted assignment to re- submit, in case the original submission is failed and/or you are asked to resubmit. Please check your Holmes email prior to reporting your assignment mark regularly for possible communications due to failure in your submission. Important Notice: All assignments submitted undergo plagiarism checking; if found to have cheated, all involving submissions would subject to penalties. Group Assignment Questions Question 1 (10 marks–2 marks for each question) 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 Question 1 sheet in HI6007 Group Assignment T1 2023 data file. |
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| Without Wait-Tracking System | With Wait-Tracking System | ||
| 24 | 31 | ||
| 67 | 11 | ||
| 17 | 14 | ||
| 20 | 18 | ||
| 31 | 12 | ||
| 44 | 37 |
| 12 | 9 | ||||
| 23 | 13 | ||||
| 16 | 12 | ||||
| 37 | 15 | ||||
| (a) What are the mean and median patient wait times for offices with a wait-tracking system? What are the mean and median patient wait times for offices without a wait-tracking system? (b) What are the variance and standard deviation of patient wait times for offices with a wait- tracking system? What are the variance and standard deviation of patient wait times for visits to offices without a wait-tracking system? (c) Create a boxplot for patient wait times for offices without a wait-tracking system. What information you can get from the boxplot? (d) Create a boxplot for patient wait times for offices with a wait-tracking system. What information you can get from the boxplot? (e) Do offices with a wait-tracking system have shorter patient wait times than offices without a wait-tracking system? Explain. Question 2 (8 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 Question 2 sheet in HI6007 Group Assignment T1 2023 data file. Using EXCEL, answer the following questions. |
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| Beer price and quantity | |||||
| Beer Price (in $/per litre) | Beer Quantity (in litres) | ||||
| 1975 | 1.85 | 191.32 | |||
| 1976 | 2.32 | 192.14 | |||
| 1977 | 2.54 | 187.13 | |||
| 1978 | 2.67 | 186.62 | |||
| 1979 | 3.09 | 182.79 | |||
| 1980 | 3.35 | 176.45 | |||
| 1981 | 3.65 | 177.44 | |||
| 1982 | 4.02 | 172.69 | |||
| 1983 | 4.58 | 171.03 | |||
| 1984 | 5.02 | 161.08 | |||
| 1985 | 5.44 | 155.14 | |||
| 1986 | 5.91 | 149.97 | |||
| 1987 | 6.52 | 150.31 | |||
| 1988 | 7.12 | 143.92 | ||
| 1989 | 7.25 | 145.88 | ||
| 1990 | 7.70 | 148.45 | ||
| 1991 | 8.32 | 146.19 | ||
| 1992 | 8.61 | 141.71 | ||
| 1993 | 8.87 | 133.26 | ||
| 1994 | 9.16 | 127.46 | ||
| 1995 | 9.44 | 125.42 | ||
| 1996 | 9.95 | 123.97 | ||
| 1997 | 10.22 | 121.84 | ||
| 1998 | 10.29 | 122 | ||
| 1999 | 10.46 | 120.59 | ||
| 2000 | 10.68 | 118.99 | ||
| 2001 | 11.63 | 117.6 | ||
| 2002 | 11.94 | 117.77 | ||
| 2003 | 12.32 | 114.28 | ||
| 2004 | 13.10 | 115.58 | ||
| 2005 | 13.69 | 111.03 | ||
| 2006 | 14.33 | 108.78 | ||
| 2007 | 14.91 | 108.79 | ||
| 2008 | 15.71 | 108.69 | ||
| 2009 | 16.41 | 108.35 | ||
| 2010 | 17.32 | 107.98 | ||
| 2011 | 17.83 | 104.94 | ||
| 2012 | 18.25 | 100.57 | ||
| 2013 | 18.62 | 96.51 | ||
| 2014 | 19.16 | 93.02 | ||
| 2015 | 19.71 | 92.38 | ||
| 2016 | 20.44 | 86.49 | ||
| 2017 | 20.99 | 89.43 | ||
| Source: Australian Bureau of Statistics | ||||
| (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. (1 mark) (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? (1 mark) |
Question 3 (22 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. Data (Question 3 sheet in HI6007 Group Assignment T1 2023 data file.) for a sample of eight markets for a recent week follow. Using this data set and EXCEL, and no more than 1500 words in total, answer the following questions.
| Market | Weekly Gross Revenue ($100s) | Television Advertising ($100s) | Newspaper Advertising ($100s) |
| Mobile | 101.3 | 5.0 | 1.5 |
| Shreveport | 51.9 | 3.0 | 3.0 |
| Jackson | 74.8 | 4.0 | 1.5 |
| Birmingham | 126.2 | 4.3 | 4.3 |
| Little Rock | 137.8 | 3.6 | 4.0 |
| Biloxi | 101.4 | 3.5 | 2.3 |
| New Orleans | 237.8 | 5.0 | 8.4 |
| Baton Rouge | 219.6 | 6.9 | 5.8 |
- 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. (1 mark)
- Develop and estimate a simple linear regression model to estimate the relationship between weekly gross revenue and television advertising expenditure. (2 marks)
- Comment on the goodness of fit of the estimated model in part (b). (1 mark)
- How do you think you can improve the goodness of fit of the estimated model in part (b) and why? (1 mark)
- Develop and estimate a multiple linear regression model to estimate the relationship between weekly gross revenue and television and newspaper advertising expenditure. (2 marks)
- What do the estimated regression coefficients in part (e) reveal about the relationship between weekly gross revenue and television and newspaper advertising expenditure? (2 marks)
- Test the overall validity/utility of the estimated multiple regression model in part (e) at the 5% level of significance. (2 marks)
- Test whether linear relationship exists between weekly gross revenue and individual independent variables in part (e) at the 5% level of significance. (2 marks)
- Will your conclusion in part (h) change if the level of significance changes to 1% level of significance? (1 mark)
- Compare the fitness of the multiple linear regression model with that of the simple linear regression model. (1 mark)
- Based on your answers to (a) to (j) 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? (7 marks)
Marking criteria
| Marking criteria | Weighting |
| Calculating central values and measure of dispersion, and developing box plots with the comparisons (Question 1). | 10 marks |
| Preparing numerical summary output and discussing on the shape of distributions (Question 2 a and b). | 3 marks |
| Performing hypothesis testings and comparing the outcomes (Question 2 c, d and e). | 5 marks |
| Developing regression model and interpret the outcomes, and testing the hypothesis based on the regression output (Question 3 a, b, c, d, e, f, g, h, I and j). | 15 marks |
| Writing a mini research report (Question 3 k) | 7 marks |
| TOTAL Weight | 40 Marks |
| Assessment Feedback to the Student: |
Your final submission is due Friday of week 10 before midnight. The following penalties will apply:
- Late submissions -5% per day.
- No cover sheet OR inaccuracies on the cover sheet -10%
- No title page -10%
- Inaccuracies in referencing OR incomplete referencing OR not in Holmes-adapted- Harvard style -10%
Student Assessment Citation and Referencing Rules
Holmes has implemented a revised Harvard approach to referencing. The following rules apply:
- Reference sources in assignments are limited to sources that provide full-text access to the source’s content for lecturers and markers.
- The reference list must be located on a separate page at the end of the essay and titled: “References”.
- The reference list must include the details of all the in-text citations, arranged A-Z alphabetically by author surname with each reference numbered (1 to 10, etc.) and each reference MUST include a hyperlink to the full text of the cited reference source.
For example:
Hawking, P., McCarthy, B. & Stein, A. 2004. Second Wave ERP Education, Journal of Information Systems Education, Fall, http://jise.org/Volume15/n3/JISEv15n3p327.pdf
- All assignments must include in-text citations to the listed references. These must include the surname of the author/s or name of the authoring body, year of publication, page number of the content, and paragraph where the content can be found. For example, “The company decided to implement an enterprise-wide data warehouse business intelligence strategy (Hawking et al., 2004, p3(4)).”
Non-Adherence to Referencing Rules
Where students do not follow the above rules, penalties apply:
- For students who submit assignments that do not comply with all aspects of the rules, a 10% penalty will be applied.
- Students who do not comply with guidelines BUT their citations are ‘fake’ will be reported for academic misconduct.
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