Applications of normal distribution: (1) Confidence intervals: x̄ ± Z×(σ/√n); (2) Hypothesis testing: Compare sample mean to population; (3) Quality control: Determine defect rates; (4) Risk assessment: Calculate probabilities; (5) Sampling distributions: Central limit theorem. Example: Sample mean 100, SD 15, n=25. 95% CI = 100 ± 1.96×(15/5) = 100 ± 5.88 = [94.12, 105.88]. Solving: Identify μ, σ, n. Standardize. Use normal table. Construct intervals. Applications: Estimation, decision-making. Exam tip: Understand margin of error. Recognize when normal approximation applies. Practice: Real-world inference problems.