Continuous Random Variables & PDFs

What this note covers

1. From Discrete to Continuous: Why We Need Density
2. Probability Density Functions: Definition and Properties
3. Computing Probabilities: P(a < X < b) as a Definite Integral
4. The Mean (Expected Value) of a Continuous Random Variable
5. The Median of a Continuous Random Variable
6. Variance and Standard Deviation of a Continuous Random Variable
7. Hybrid and Piecewise PDFs, and Exam Technique

7 sections · 14 key terms & formulas · 6 common mistakes