HA1011 Applied Quantitative Methods T3 2024 Assessment

Group Assignment

Group Assignment Guidelines and Specifications

Instructions:

• Your assignment report must be submitted in WORD format only. However, you are required to attach the excel file to support your answers.
• 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.
• 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.

Group Assignment Questions

Part A                                                                                                                                                                                   (10 marks)

For this group assessment, you will analyze data from the Australian Bureau of Statistics (ABS) on "Average Weekly Ordinary Time Earnings, Full-time Adults by State," with a focus on weekly earnings disaggregated by gender. Your task is to explore the patterns and trends in earnings across different states and gender groups. As a group, you will apply appropriate quantitative methods covered in class to present your findings in a concise report, demonstrating your ability to interpret and communicate the results of your analysis clearly and effectively.

1. You are required to present this data in a suitable graphical format. (3marks)
2. Comment on the key observations to identify key trends, differences between Male and Female. (3marks)
3. Comment on the key observations to identify key trends, differences between the States. (2 marks)

4. Suggest potential factors influencing these variations between the States. (2 marks)

    

Note: Refer the data given the excel file “Data Set for Part A_Average Weekly ordinary time earnings, full- time adults by state”

Part B                                                                                                                                                                                   (30 marks)

You are tasked with analyzing the determinants of weekly rent prices for houses across various regions in Australia. The primary objective of this assessment is to identify and investigate the factors that influence weekly rent prices and develop a predictive model to estimate rents based on these variables.

Instructions:

Data Collection:

• Collect data from a sample of at least 40 houses available for rent. The sample should be based on the state and city where your campus is located.
  • The data should pertain to houses listed for rent from July 1st onwards.

Variables to Record:

For each property, you are required to collect the following information:

• Weekly Rent: The rent being asked for the property per week.
  • Number of Bedrooms: The total number of bedrooms in the property.
  • Distance to the Nearest Primary School: Measured in kilometres or meters, depending on the data available.
  • Property Type: Specify whether the property is a House, Townhouse, Apartment, Unit, or Villa.
  • Hyperlink to Advertisement: Provide the URL of the online listing where the property is advertised.
  • Property Address: This will help in verifying the validity and location of the data.

Guidelines:

• Ensure the accuracy and consistency of your data.
  • Pay particular attention to the reliability of the advertisement hyperlinks and the correctness of addresses. This will be essential for assessing the validity of your data and ensuring the sample represents properties available in the area.

(5 marks)

Once the data is collected, you will use it to answer the following questions:

i.Conduct descriptive statistical analysis on the collected data, including measures of central tendency, dispersion, and graphical representations to summarize the characteristics of the variables.

(5 marks)

ii,Calculate the correlation coefficients between weekly rent and each of the independent variables (number of bedrooms, distance to the nearest primary school), and discuss the strength and direction of the relationships between weekly rent and determinants of weekly rent.

(5 marks)

iii. Perform simple linear regression analysis with weekly rent as the dependent variable and each independent variable (Number of bedrooms, distance to the nearest primary school) separately. Based on your regression outputs from Excel, answer the following questions.

a.  Comment on the coefficient of determination (R-squared) and the standard error of the estimate for each regression model.

b. Interpret the regression results and discuss the predictive power of each independent variable on weekly rent.

c. Assess the significance of the independent variable in each model.

(10 marks)

vi.Prepare a brief report that reflects your findings based on the answers to questions I through IV.

Note: Your report should primarily focus on the identified relationships and other key observations from your analysis.

(5 marks)

Note: Analysis should be performed in Microsoft Excel ONLY.

Marking criteria

Marking Rubric

Your final submission is due Wednesday of Week 9 before midnight.
 

The following penalties will apply:

1. Late submissions -5% per day.
2. No cover sheet OR inaccuracies on the cover sheet -10%
3. No title page -10%
4. Inaccuracies in referencing OR incomplete referencing OR not in Holmes-adapted- Harvard style -10%
5. Appendix missing or incomplete or not in prescribed format -10%

Student Assessment Citation and Referencing Rules

Holmes has implemented a revised Harvard approach to referencing. The following rules apply:

1. Reference sources in assignments are limited to sources that provide full-text access to the source's content for lecturers and markers.

2. The reference list must be located on a separate page at the end of the essay and titled: "References".

3. The reference list must include the details of all the in-text citations, arranged A-Z alphabetically by author's 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:

1. Hawking, P., McCarthy, B. & Stein, A. 2004. Second Wave ERP Education, Journal of Information Systems Education, Fall, http://jise.org/Volume15/n3/JISEv15n3p327.pdf

4. 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:

1. For students who submit assignments that do not comply with all aspects of the rules, a 10% penalty will be applied.
2. Students who do not comply with guidelines BUT their citations are 'fake' will be reported for academic misconduct

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