Analysis
Optimize Pricing for a Sydney D2C Cosmetics Brand
Overview
What this challenge is about.
You are a junior data analyst at GlowSydney. Using the provided dataset of 500 transactions (including price, units sold, customer age, and gender), perform descriptive statistics to understand the distribution of prices and quantities. Then, conduct a simple linear regression to model the relationship between price and quantity demanded. Estimate the price elasticity of demand and determine the revenue-maximizing price. Present your findings in a 2-page report with visualizations and a clear recommendation. Success is defined by a well-justified price recommendation supported by statistical evidence.
The Brief
What you'll do, and what you'll demonstrate.
Determine the optimal price for a new moisturizer to maximize revenue, using historical transaction data and regression analysis.
Earning criteria — what you'll demonstrate
- Apply descriptive statistics to summarize a dataset
- Perform simple linear regression to model a relationship
- Interpret regression coefficients and R-squared
- Calculate and interpret price elasticity of demand
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career mappings coming soon.