STAT 340
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Probability and Inference 2
Course Description
Transformations of random variables; sampling distributions; Central Limit Theorem; frequentist inference (estimation, intervals, hypothesis tests); Bayesian inference (estimation, intervals); simulation.
When Taught
Fall; Winter.
Min
3
Fixed/Max
3
Fixed
3
Fixed
0
Recommended
Stat 123 and Stat 124
Title
Transformations
Learning Outcome
Find the distribution of a transformation of random variables, including the Chi-squared and derived distributions t and F.
Title
Sampling Distributions
Learning Outcome
Explore the sampling distributions for means and totals of random samples from common distributions.
Title
Convergence
Learning Outcome
Apply convergence in probability and distribution to prove the Law of Large Numbers and participate in proving the Central Limit Theorems for means and proportions.
Title
Sufficiency
Learning Outcome
Find sufficient statistics in one-parameter problems.
Title
Point Estimation
Learning Outcome
Derive method of moments, maximum likelihood, and Bayesian estimators.
Title
Interval Estimation
Learning Outcome
Construct confidence intervals using pivots and credible intervals.
Title
Hypothesis Testing
Learning Outcome
Apply the Neyman-Pearson lemma to derive the critical region for problems involving simple hypotheses.
Title
Evaluation
Learning Outcome
Evaluate point estimators with respect to bias, variance, and MSE.
Title
Simulation
Learning Outcome
Examine sampling distributions and evaluate estimators using simulation.
Title
Critical Thinking
Learning Outcome
Increase analytical confidence and critical thinking skills.
