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Linear Statistical Inference/
Linjära statistisk inferens

Number of credits: 8 hp

Examiner: Dietrich von Rosen and Martin Singull

Course literature: C. R. Rao - Linear Statistical Inference and Its Applications (2nd Ed.)

Course contents: Chapters 5-7 in the course book. * Criteria and Methods of Estimation - Minimum Variance Unbiased Estimation, Fisher's Information Measure, Principle of Invariance, Consistency, Efficiency, Method of Moments, Maximum Likelihood, Method of Scoring * Large Sample Theory and Methods - Asymptotic Distribution of Quadratic Functions, Chi-Square Test, Contingency Tables, Large Sample Tests, Order Statistics, Transformation of Statistics * Theory of Statistical Inference - Testing of Statistical Hypotheses, Confidence Intervals, Sequential Analysis, Decision Theory, Nonparametric Inference, Ancillary Information.

Organisation: Lectures and compulsory assignments.

Examination: Hand in problems.

Prerequisites: Basic courses in probability theory, statistical inference, linear algebra and the first course Linear Statistical Models (MAI0109).

Page manager: karin.johansson@liu.se
Last updated: 2022-11-15