ECON10005 – Quantitative Methods I

Data Analysis Report

2025 Semester 1

1. Purpose

This assessment task allows students to critically analyse real-world data and present their findings as a data analysis report. This task prepares students for the requirements of many business graduates employed within the public and private sectors. By completing this task, students are expected to develop their critical and creative thinking skills, presentation and written articulation of quantitative arguments, and collaborative skills.

2.   General Instructions to Students

●   Read all instructions in this document carefully.

●   The first Draft Task carries 3% of the total assessment for ECON10005.

● This is a compulsory group assignment: your tutor will put you into groups of four students from the same tutorial during week 3 tutorials. Please attend the tutorial you are registered for to facilitate the grouping. Individual assignments will not be accepted for this subject.

●   The first draft has a word limit of 700 words.

o No penalty for submissions with a word count within 10% of the word limit.

o Graphs, tables, equations and appendices do not count toward the word limit, provided they do not contain substantive explanation, analysis, or discussion.

●   All submissions are checked for plagiarism and originality. Students should be familiar with the university’s academic integrity policy, available here.

o Explanation, analysis, or discussion generated by AI software (including ChatGPT) is not permitted in this assessment. More details are here.

●   Students should rely only on the material discussed in Weeks 1 and 2 lectures in   preparing this report. All statistical analyses should be conducted using Microsoft Excel.

o Students are not required (nor would it be advantageous) to consult external material or provide a reference list.

●   Students may use the Ed Discussion Board to clarify questions about this assignment.

o Students should NOT upload parts of their assignment (including calculations and written work) or discuss their exact approach to the assignment on the Ed Discussion Board.

3. Submission Guidelines

●   Assignment Submission

o Submissions must be made using the link on Canvas before the deadline (4 p.m., Monday, 31 March).

n Late submissions will receive no feedback and a mark of zero.

n Students needing extensions for legitimate reasons must apply for an extension/special consideration. Information can be found in the subject guide. A faculty team oversees these applications.

n Issues about formatting or incorrect/incomplete versions of submitted assignments are not considered valid grounds for an extension.

o Student should submit two documents and a short survey for this assignment:

n A PDF file with answers to the tasks described below (report).

n An Excel file with the data and all the workings (descriptive statistics and graphs). Every graph and descriptive statistic created for the report should be included with clear labels in this Excel sheet.

n A short survey assessing each member’s contributions.

o Students should refer to the Subject Guide (available on Canvas) for the extension policy applicable to this assignment.

● Assignment Formatting

o The report should include a cover page with your Student ID, tutorial time and location, and tutor’s name.

o The report must be typed and compiled into a PDF before submission.

n The  PDF  file  should  have  all  (and  only)  relevant  graphs  and  figures included.

n In your writing, make sure to provide references to the tables and figures you use. Here is an example, “ … . as presented in Table 2, the mean of variable X (mean = xx) is higher than the mean ofY (mean = yy)” .

n Handwritten assignments will not be marked, and any handwritten additions (including  graphs  or  equations) to  otherwise typed  assignments will be ignored.

n Please make sure to label the graphs and tables correctly.

o Excel file should be submitted without converting to PDF or any other format.

4. The Task

You are a property market analyst working for a real estate investment firm that specialises in identifying trends in the Melbourne housing market. Your task is to analyse a random sample of 999 recently sold houses to uncover key insights about property values and the factors influencing them. The dataset includes the selling price of each property (in thousands of dollars), its distance from the CBD, the dwelling size, and the land size.

Your analysis will help investors and homebuyers make informed decisions about Melbourne’s housing market. By exploring relationships between price, location, and property size, you will provide valuable insights into what drives property values and how different factors shape market trends.

Here is a description of the data:

Price:               Selling price (in thousands of dollars).

Distance:         Distance from the CBD (in kilometres).

Bld area:         Dwelling size (square metres).

Landsize:        Land size (square metres).

Large:              Whether the property is on a large lot (1 = Yes, 0 = No).

CBD:               Whether the property is in the CBD area (1 = Yes, 0 = No).

Here is the structure of the data analysis report:

1. Title: Give an interesting title to your report

2. Introduction- 100 words

●   Briefly introduce the purpose of your report.

●   Explain what the dataset is about and what insights you aim to uncover.

3. Data Exploration (Complete this section using Task 1 and Task 2 below)- 300 words

●   Provide a summary of key statistics for each variable.

●   Use graphs (such as histograms, box plots, etc.) to explore information in the data visually.

4. Analysis of house prices (Complete this section using Tasks 3 and 4 below)- 250 words

●   Investigate how different factors influence price. For example:

o Does distance from the CBD affect property prices?

o Do larger properties tend to be more expensive?

o Do houses closer to the CBD tend to be smaller/larger than those farther away?

5. Summary and Conclusion- 50 words

●   Provide a brief conclusion summarising your key insights.

●   Suggest any further questions or areas for future investigation.

Note: Each student should attempt to complete all four tasks below, discuss them among the group, and then write the report.

Task 1:

●   Provide the summary statistics and at least one appropriate graphical method to describe the distribution of house prices. Compare and contrast these statistics. Ensure that the following information is provided.

o A summary statistics table including the sample size, mean, median, standard deviation, range, interquartile range, minimum, maximum and 90th  percentile for the price.

o A histogram and a box plot to visually describe the distribution of the price.

o An  approximately  100-word  explanation  of  the  descriptive   statistics  and distribution of the price and any other interesting/noteworthy features.

Task 2:

●   Provide appropriate  summary statistics and graphs to describe the other variables (distance, dwelling size, land size, whether the property is large or not and if the property is in the CBD area or not). Ensure that the following information is provided.

o A summary statistics table including the sample size, mean, median, standard deviation, range, interquartile range, minimum, maximum and 90th  percentiles (note: calculating all these summary statistics may not be meaningful for the qualitative variables, choose the appropriate ways to summarise them).

o A graph for each variable to present the distribution for the variables

o An  approximately 200-word  explanation of the descriptive statistics and distribution of the variables and any other interesting/noteworthy features.

Task 3:

●   Use descriptive statistics and graphical methods to present similarities/differences in the prices by the property’s distance from the CBD, dwelling size, land size, if the property is branded as large or not, and if the property is in the CBD area or not.

o Use an appropriate graph and a measure of association to show the relationship between house price and the distance to CBD.

o Use an appropriate graph and a measure of association to show the relationship between house price, land size, and dwelling size (note: you are creating two graphs here, one for price vs. land size and another for price vs. dwelling size).

o Calculate two sets of descriptive statistics for house prices based on whether they are in the CBD area or not (column F in the Excel file).

o Calculate two sets of descriptive statistics for house prices based on whether the house is deemed large (column E in the Excel file).

o An  approximately  150-word  explanation  of the  relationship between house price and other variables you have looked at.

Task 4

●   An   analysis  of  the  relationship  between   the   distance  of  the  property   and  the land/dwelling size:

o Using appropriate graphs, show the relationship between the distance of the property from the CBD and the land size and the dwelling size (note: you are creating two graphs here, one for distance vs land size and another for distance vs dwelling size).

o An assessment of the  strength of the relationships, defended by appropriate descriptive statistics.

o An  approximately  100-word  explanation  of  the  relationship  between  the distance of the property from CBD and its size using the statistics and the graphs you have above.