Transcription of Mathematical Statistics, Lecture 2 ... - MIT OpenCourseWare
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Mathematical Statistics, Lecture 2 ... - MIT OpenCourseWare
Statistical Models Statistical Models MIT Dr. Kempthorne Spring 2016 1 MIT Statistical Models Statistical Models Definitions Examples Modeling Issues Regression Models Time Series Models Outline 1 Statistical Models Definitions Examples Modeling Issues Regression Models Time Series Models 2 MIT Statistical Models Statistical Models Definitions Examples Modeling Issues Regression Models Time Series Models Statistical Models: Definitions Def: Statistical Model Random experiment with sample space . Random vector X = (X1, X2,.., Xn) defined on . : outcome of experiment X ( ): data observations Probability distribution of X X : Sample Space = {outcomes x}FX : sigma-field of measurable events P( ) defined on (X , FX ) Statistical Model P = {family of distributions } 3 MIT Statistical Models Statistical Models Definitions Examples Modeling Issues Regression Models Time Series Models Statistical Models: Definitions Def: Parameters / Parametrization Parameter identifies/specifies distribution in P.
Response variable Y (specify the scale) Explanatory variables X. 1, X. 2,... X. p (include different functions of explanatory variables if appropriate) Assumptions about the distribution of E over the cases (2) Specify/define a criterion for judging different estimators. (3) Characterize the best estimator and apply it to the given data.
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