Mat-243 | Project 2

This is typically a Jupyter Notebook project in Python (using pandas, numpy, scipy.stats, matplotlib, seaborn) where you analyze a dataset — often NBA player stats or something similar — and perform hypothesis testing, confidence intervals, and data visualization.

wins_new = new_team['won'].sum() wins_hist = historical_team['won'].sum() n_new = len(new_team) n_hist = len(historical_team) mat-243 project 2

Many students lose points not because their code fails, but because their is weak. The Jupyter Notebook typically includes markdown cells where you must explain: This is typically a Jupyter Notebook project in

| Pitfall | Solution | |--------|----------| | Using ttest_ind without alternative | Default is two-tailed. For Project 2’s first test, use alternative='greater' . | | Forgetting ddof=1 in np.std | This calculates sample standard deviation, not population. | | Misinterpreting p-value | P-value is not the probability that H₀ is true. It’s P(data | H₀). | | Copying code without understanding | The Codio autograder checks variable names exactly. Use historical_relative_skill not hist_skill . | | Skipping assumptions | Mention the Central Limit Theorem (n > 30) to justify normality. | For Project 2’s first test, use alternative='greater'