FIN10002: Financial Statistics Assignment 2

Assignment Overview

For this assignment, you are required to produce a report responding to eight tasks presented in Part A and Part B. The submission will be in two installments: Part A and Part B.

Some sections require Excel and Python to generate statistical output, including tables, summary statistics, and graphs. The final report should be written as a business report for a senior manager, who is not assumed to have prior knowledge of statistical methods.

Software to be used:

• Microsoft Word (for the report)

• Excel (for calculations and graphs)

• Python (for statistical analysis)

• Presentation software (PowerPoint or similar)

• Video software (for presentation summarizing results)

Submission Requirements:

1. Excel file with statistical analyses and graphs

2. ZIP file containing Python files

3. PDF version of the report, including a link to your video presentation

Important: Statistical calculations must be done using Excel and Python only.

Data Set Details

You will use the Excel dataset: Major Assignment Data.xlsx

• Link: Download Dataset

• Contains 20,790 property sales in Melbourne (Jan 2022 – Mar 2024)

• Variables (9):

  1. Type: h = house/cottage/villa/semi-detached/terrace; u = unit/duplex; t = townhouse

  2. Price: in Australian Dollars

  3. Method of Sale: S = Sold, SP = Sold prior to auction, PI = Passed in, Vendor bid, SA = Sold after auction

  4. Date: sale date

  5. Distance: from CBD in kilometres

  6. Bedrooms: number of bedrooms

  7. Bathrooms: number of bathrooms

  8. Car Space: number of car spaces available

  9. Region: geographic region of Melbourne

This dataset will be used to generate responses to the eight tasks in Part A and Part B.

Part A – Tasks Overview

Task 1: Random Data Sample

• Select a random sample of 200 transactions from the dataset.

• This sample will be used for all tasks in both Part A and Part B.

• Important: Do not use the random generator in Data Analysis; use an alternative technique.

• Supporting Video: Task 1 Guidance

Task 2: Descriptive Statistics

• Use data summary methods to describe your sample for all nine variables.

• Include tables and graphs in Excel:

  • At least two tables (frequency tables or descriptive statistics)

  • Five variables must also have a table and graph in Python

Techniques to Use:

• Tabular: frequency tables, grouped frequency tables

• Summary Statistics: mean, median, mode, standard deviation, range, coefficient of variation, interquartile range

• Graphical: pie chart, bar graph, histogram, frequency polygon

Task 3 (Brief Intro for Report)

• Task 3 instructions will build on Task 2 results and involve further analysis using Excel and Python.

• Focus on clarity and visual presentation suitable for a senior manager.

Assessment Requirements – Brief Summary

The assessment required the production of a comprehensive business report responding to eight tasks across Part A and Part B, submitted in two installments. Key requirements included:

• Data Analysis: Using Excel and Python to generate statistical outputs such as tables, summary statistics, and graphs.

• Report Format: Written as a business report for a senior manager with no assumed statistical knowledge.

• Software Requirements: Microsoft Word, Excel, Python, PowerPoint (or similar), and video software for a presentation summarizing results.

• Submission Components:

  • Excel file with calculations and graphs

  • ZIP file containing Python files

  • PDF version of the report with a link to a video presentation

• Dataset: Major Assignment Data.xlsx, containing 20,790 property sales in Melbourne (Jan 2022 – Mar 2024) with nine variables: Type, Price, Method of Sale, Date, Distance, Bedrooms, Bathrooms, Car Space, and Region.

• Tasks Overview:

  1. Task 1: Select a random sample of 200 transactions from the dataset (without using the standard Excel random generator).

  2. Task 2: Perform descriptive statistics for all nine variables using tabular, summary, and graphical methods.

  3. Task 3: Build on Task 2 results to perform further analysis and present findings clearly for a senior manager.

The main objective was to demonstrate data analysis, interpretation, and presentation skills, aligned with unit learning outcomes 1–5.

Assessment Approach – Academic Mentor Guidance

The Academic mentor guided the student step by step, ensuring a structured and efficient approach to complete the assessment:

Step 1: Understanding the Requirements

• The mentor reviewed the dataset and assignment brief with the student, explaining the objectives of each task and the importance of presenting data clearly for a managerial audience.

• Emphasis was placed on understanding the types of variables and the appropriate statistical techniques to use for each.

Step 2: Task 1 – Random Data Sample

• The mentor explained alternative methods to select a random sample of 200 transactions without using the standard Excel random generator (e.g., random row selection using formulas or Python sampling).

• The student generated the sample, which formed the basis for all subsequent analyses.

Step 3: Task 2 – Descriptive Statistics

• The mentor guided the student in Excel to:

  • Create frequency tables for categorical variables

  • Generate summary statistics (mean, median, mode, standard deviation, range, coefficient of variation, interquartile range) for numerical variables

  • Draw graphs (pie charts, bar graphs, histograms, frequency polygons) to visualize the data

• The mentor then introduced Python techniques for statistical analysis:

  • Using Pandas and Matplotlib/Seaborn to recreate tables and graphs for five selected variables

• The focus was on consistency between Excel and Python outputs and clarity of presentation.

Step 4: Task 3 – Extended Analysis

• Building on the descriptive statistics, the mentor demonstrated how to interpret the results to identify trends, patterns, and insights.

• Guidance was provided on presenting the analysis clearly for a non-technical audience, emphasizing:

  • Use of visual aids to support findings

  • Writing concise explanations of statistical results

  • Highlighting key business insights such as pricing trends, regional differences, and property type analysis

Step 5: Preparing the Report and Presentation

• The student compiled all analyses into a professional business report using Word.

• Instructions were given to embed charts, tables, and Python outputs, ensuring visual clarity.

• The mentor guided the creation of a video summary of key findings for submission alongside the report.

Outcome Achieved

• A complete report covering all eight tasks, clearly presented for a senior manager.

• Excel and Python outputs aligned, demonstrating accurate statistical analysis.

• Visualizations and tables effectively communicated insights from the dataset.

• A video presentation summarizing the report findings was successfully included.

Learning Objectives Covered

Through this assessment, the student achieved the following:

1. Data Analysis Skills: Applying Excel and Python to generate statistical outputs.

2. Interpretation Skills: Translating complex statistical data into actionable business insights.

3. Communication Skills: Presenting results clearly in a business report format.

4. Technical Competence: Using tabular, summary, and graphical methods correctly.

5. Problem-Solving: Approaching the dataset methodically, selecting appropriate samples, and performing relevant analyses.

Boost Your Assignment Success with Reference Solutions

Looking for guidance to tackle your assignments effectively? Our sample solution provides a clear reference to help you understand how to structure your work, present data, and approach questions. Remember: This sample is for reference purposes only. Submitting it as your own work constitutes plagiarism and can have serious academic consequences.

Want a completely original, plagiarism-free solution tailored to your requirements? Our team of professional academic writers can craft a fresh assignment from scratch, ensuring it meets your course criteria while giving you peace of mind.

Why Order a Fresh Assignment?

• 100% original content written to your instructions

• Fully plagiarism-checked for academic integrity

• Expertly structured and formatted for top grades

• Delivered on time with clear explanations and insights

Take the safe and smart approach: use our sample for reference, or get a custom solution written just for you.

Download Sample Solution   Order Fresh Assignment