Statistics (STAT 101) Central Limit Theorem + Sampling Distributions Formula Sheet and Practice
University of Florida
Statistics (STAT 101) | Practice Problems

Overview
A CLT-focused packet that builds intuition for sampling distributions, standard error, and when normal approximations are valid, with short practice prompts.

Key topics
•sampling distribution of the mean
•central limit theorem conditions
•standard error and sample size effects
•z-scores for sample means
•normal approximation checks

Suggested study tasks
•compute standard error for multiple sample sizes
•decide if CLT applies in a scenario
•convert a probability question into a z-score
•interpret what a sampling distribution describes

Common pitfalls
•treating the sampling distribution like the original data distribution
•using CLT for tiny samples with heavy skew
•forgetting to adjust for n when computing standard error
•confusing population sigma with sample s