HI6007 Statistics for Business Decisions T2 2025 Assessment 

Group Assignment

Group Assignment Guidelines and Specifications

PARTA(25marks)

You are part of the data analytics team at a leading Australian consulting firm. The company serves a diverse client base including public listed companies, small medium sized enterprises (SMEs), and educational institutions. Your team has been assigned to investigate factors influencing property prices in the Australian real estate market to assist stakeholders in making informed business decisions.

Research Question

How do different factors, such as land size, number of bedrooms, distance to the nearest secondary school, and number of garage spaces, influence the selling price of residential properties?

Task

Your task is to analyze this question using Analysis of Variance (ANOVA) and Correlation Analysis. You must collect real-world data, analyze it using appropriate statistical methods, and interpret your results in a business context.

1. Data Collection Task (5marks)

Create a data set in Excel that meets the following criteria (You are required to upload the data file separately).

1. At least 100 observations.

1. Variables to include Selling Price (AUD), Land Size (s q m), Number of Bedrooms, Distance to Nearest Secondary School (km), and Number of Garage Spaces
   1. All properties must have been sold on orafter01/08/2025.

1. For verification, provide a hyperlink to each property’s original listing format rusted real estate website.

1. Descriptive Statistics and Visualization                                                               (8 marks)

1. Descriptive Statistics Table (2marks)

Using Excel, generate and present the following statistics for each variable: Mean, Median, Mode, Variance, Standard Deviation, Skewness, Kurtosis, and Coefficient of Variation.

1. Commentary on Descriptive Statistics in 2(I) above (2marks)

Interpret the values from the descriptive statistics. Discuss the distribution of each variable and identify any interesting patterns, skew ness or out liers that may affect analysis or business decisions.

1. Graph–Distribution of Bedrooms (2marks)

Useanappropriategraphtovisualisethenumberofbedrooms.Provideabriefexplanationofwhat this distribution indicates.

1. Graph–Land Size vs. Selling Price (2marks)

Create an appropriate graph to illustrate the relationship between land size and selling price. Briefly comment on the relationship.

1. Inferential Analysis : ANOVA and Correlation                                                   (12marks)

2. One-Way ANOVA–Bedrooms vs. Selling Price (8marks)

Use Excel’s ANOVA tool to assess whether the mean selling price differs significantly based on the number of bedrooms.

• Clearly state the null and alternative hypotheses in the context of the relationship between number of bedrooms and selling price. (1 mark)
  • Present the F-statistic, p-value, and your decision based on a 5% significance level. (2mark)

• Interpret the results and explain whether bedroom count is a significant factor in pricing decisions. (2 mark)
  • Based on your ANOVA results, state whether a post hoc analysis is warranted. If it is, list appropriate post hoc tests .Then, perform one suitable post hoc test, and interpret the result in relation to pricing strategy. (3 marks)

• Correlation Analysis (4marks)

Produce a correlation matrix for all quantitative variables.

• Identify strength and direction of relationships with selling price. (1mark)

• Highlight any potential multi collinearity among independent variables. (1mark)
  • Provide brief insights into what this implies for business or property investment decisions. (2 marks)

Part B– Employment and Unemployment Trends Analysis                         (10marks)

Business Scenario

You are part of a consulting group analysing long-term labour market trends in Australia. Your team must apply a mix of statistical tools to evaluate gender-based differences in employment and unemployment types, with a focus on how such data informs workforce planning and policy recommendations.

Data Variables (1979–2024)

• Male and Female Full-time Employment

• Male and Female Part-time Employment

• Male and Female Total Unemployment

• Male and Female Unemployed looking for Full-time Work

• Male and Female Unemployed looking for Only Part-time Work

Research Question:

How have gender-based differences in employment and unemployment patterns evolved in Australia

From 1979 to 2024. What are the statistical and policy implications of these trends?

Task

Note: Refer to the data given in the Excel file “HIM6007T22025GroupAssessment-Dataset”

1. Confidence Interval Estimation & Hypothesis Testing (6marks)

1. Confidence Intervals (3marks)

• Estimate 95% confidence intervals for females unemployed seeking only part-time work and Males unemployed seeking only part-time work
  • Discuss over lap and implications for work force dynamics.

1. Hypothesis Test (3marks)

• Test whether females unemployed and looking for full-time work differ significantly in average number compared to males.
  • State hypotheses, perform t-test, report p-value, and interpret the business relevance.

1. Probability & Socio economic Interpretation (4marks)

• Calculate the probability that a randomly selected unemployed individual is a female seeking only part-time work.
• Link statistical findings to labour market theories and discuss implications for business or policy.

Part C–Summary of your analysis addressing the research question              (5 marks)

1. Based on the answers in PARTA above, write a summary of your analysis addressing the research question (100 -150 words). (3 marks)
2. Based on the answers in PARTB above, write a summary of your analysis addressing the research question (100 words). (2 marks)

Submission Checklist

1. Each member must contribute to data collection, analysis, and report writing.

1. In your submission, include a brief note detailing each member’s contributions.

1. Attach:
   • MS Word report
     • Excel spread sheets with raw data and analysis
     • Data source hyperlinks

Marking criteria

Your final submission is due Friday of week ten before midnight.

The following penalties will apply:

1. Late submissions-5%perday.
2. Inaccuracies in referencing OR incomplete referencing OR not in Holmes-adapted- Harvard style -10%
3. Solo Grouppenalty-20%

Student Assessment Citation and Referencing Rules

Holmes has implement da 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.

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

1. 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 (1to10, 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

1. 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 (Hawkingetal., 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