HI6007 Statistics for Business Decisions T2 2025 Assessment
Group Assignment
| Assessment Details and Submission Guidelines | |
| Trimester | T22025 |
| Unit Code | HI6007(BlockMode2) |
| Unit Title | Statistics for Business Decisions |
| Assessment Type | Group Assignment |
| Weight | 40% |
| Submission Guidelines |
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| Penalties |
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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.
Data Collection Task (5marks)
Create a data set in Excel that meets the following criteria (You are required to upload the data file separately).
- At least 100 observations.
- 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
- All properties must have been sold on orafter01/08/2025.
- For verification, provide a hyperlink to each property’s original listing format rusted real estate website.
Descriptive Statistics and Visualization (8 marks)
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.
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.
Graph–Distribution of Bedrooms (2marks)
Useanappropriategraphtovisualisethenumberofbedrooms.Provideabriefexplanationofwhat this distribution indicates.
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.
One-Way ANOVA–Bedrooms vs. Selling Price (8marks)
Inferential Analysis : ANOVA and Correlation (12marks)
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”
- Confidence Interval Estimation & Hypothesis Testing (6marks)
- 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.
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.
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)
- Based on the answers in PARTA above, write a summary of your analysis addressing the research question (100 -150 words). (3 marks)
- Based on the answers in PARTB above, write a summary of your analysis addressing the research question (100 words). (2 marks)
Submission Checklist
- Each member must contribute to data collection, analysis, and report writing.
- In your submission, include a brief note detailing each member’s contributions.
- Attach:
- MS Word report
- Excel spread sheets with raw data and analysis
- Data source hyperlinks
- MS Word report
Marking criteria
| Marking criteria | Weighting |
| PARTA(25marks) | |
| Data collection (Excel spreadsheet) | 5marks |
| Descriptive statistical analysis and review(Questions2i–iv) | 8marks |
| ANOVA and Correlation output and interpretation (Questions 3 I and ii) | 12marks |
| PART B (10marks) | |
| Confidence Interval Estimation & Hypothesis Testing (Question i) | 4marks |
| Probability & Socio economic Interpretation (Question ii) | 6marks |
| PARTC(5marks) | |
| Summary (I and ii) | 5marks |
| TOTAL Weight | 40Marks |
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Assessment Feedback to the Student: |
| Criterion | Excellent(HD) | Very Good(D) | Good (C) | Satisfactory(P) |
Unsatisfactory (F) |
| PARTA–Data Analysis(25Marks) | |||||
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1. Data Collection (Excel spreadsheet) (5 marks) |
Data is complete, Accurately entered, well-organized and labelled; clearly reflects a strong Understanding of data preparation. |
Data is mostly complete and well-organized, with only minor errors or omissions. |
Data is generally accurate but may include some formatting or organization issues. |
Basic data is included, but errors or lack of structure reduce clarity. |
Data is In accurate, incomplete, disorganized, or missing. |
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2. Descriptive Statistical Analysis & Review (Questions2 i– iv)(8 marks) |
Outstanding Application of Descriptive statistics (mean, median, mode, SD, etc.); Comprehensive review and accurate interpretation of all measures. |
Very good application and interpretation with only minor misinterpretations. |
Good analysis with adequate statistical measures and generally correct interpretation. |
Basic understanding shown; some correct statistics but interpretation is limited. |
Poor or incorrect Use of statistics; no meaningful interpretation. |
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3.ANOVAand Correlation Output & Interpretation (Questions 3 I & ii)(12marks) |
Demonstrates deep Understanding of both ANOVA and Correlation analysis; accurate output, insightful and correct interpretation of relationships. |
Very good Understanding with mostly accurate output and interpretation; minor gaps. |
Good understanding with correct output but limited interpretation or minor errors. |
Basic interpretation: output may contain errors or misinterpretations. |
Poor or incorrect output; no understanding of statistical meaning or relationships. |
| PARTB–Statistic alI nference (10Marks) | |||||
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4. Confidence Interval Estimation & Hypothesis Testing (Question i)(4 marks) |
Excellent Understanding and execution of CI and hypo thesis testing; correct values and insightful interpretation in context. |
Very good use of Methods with Correct calculation and mostly clear interpretation. |
Good attempt With some Correct results and partial interpretation. |
Basic attempt made; multiple errors in method or interpretation. |
In corrector missing calculation; misunderstanding of statistical inference. |
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5.Probability& Socioeconomic Interpretation (Question ii)(6 marks) |
Accurate and well- Reasoned probability analysis; strong Link age to Socio economic context with clear insight. |
Very good probability estimation and generally relevant interpretation. |
Good attempt; minor issues with calculations or socio economic relevance. |
Basic probability analysis; interpretation may be vague or underdeveloped |
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