Continuous and Normal Models

Why this chapter matters

Many measured quantities are continuous, and normal approximations provide practical probability calculations and benchmarks.

What you will learn

• Explain the difference between probability at a point and over an interval for continuous data.
• Standardize values with z-scores and interpret relative position.
• Compute normal probabilities and percentiles from model parameters.

Lessons in this chapter

1. Continuous random variablesInterpret area under a density curve as probability.
2. Normal distributions and z-scoresConvert between raw values and standardized scores.
3. Normal probability calculationsFind interval probabilities and cutoff values using normal models.
4. Model fit and reasonablenessCheck whether a normal model is plausible from data shape and context.

Study task

Chapter checkpoint