midProbability
What is the difference between discrete and continuous random variables in modeling?
Updated May 17, 2026
Short answer
Discrete variables take countable values; continuous variables take values from intervals.
Deep explanation
Discrete variables are modeled using PMFs and are used for counts, categories, or events. Continuous variables use PDFs and model measurements. The mathematical treatment differs fundamentally in probability computation.
Real-world example
Number of customers (discrete) vs time spent in app (continuous).
Common mistakes
- Treating continuous variables like discrete ones when calculating probabilities.
Follow-up questions
- Can a variable be both?
- Why does modeling choice matter?