ENGG40Probatatisticsfoer Chapter 8 Bayesian Statistical Inference Instructor:Shengyu Zhang
Instructor: Shengyu Zhang
Statistical inference Statistical inference is the process of extracting information about an unknown variable or an unknown model from available data. Two main approaches Bayesian statistical inference 0 Classical statistical inference
Statistical inference Statistical inference is the process of extracting information about an unknown variable or an unknown model from available data. Two main approaches Bayesian statistical inference Classical statistical inference
Statistical inference Main categories of inference problems oparameter estimation hypothesis testing significance testing
Statistical inference Main categories of inference problems parameter estimation hypothesis testing significance testing
Statistical inference Most important methodologies ▣maximum a posteriori(MAP)） probability rule, o least mean squares estimation, omaximum likelihood. ▣regression, o likelihood ratio tests
Statistical inference Most important methodologies maximum a posteriori (MAP) probability rule, least mean squares estimation, maximum likelihood, regression, likelihood ratio tests
Bayesian versus Classical Statistics Two prominent schools of thought oBayesian Classical/frequentist. Difference:What's the nature of the unknown models or variables? Bayesian:they are treated as random variables with known distributions. ■ Classical/frequentist:they are treated as deterministic but unknown quantities
Bayesian versus Classical Statistics Two prominent schools of thought Bayesian Classical/frequentist. Difference: What’s the nature of the unknown models or variables? Bayesian: they are treated as random variables with known distributions. Classical/frequentist: they are treated as deterministic but unknown quantities