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HU Credits:
6
Degree/Cycle:
1st degree (Bachelor)
Responsible Department:
Statistics
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
Mt. Scopus
Course/Module Coordinator:
Pavel Chigansky
Coordinator Office Hours:
by appointment
Teaching Staff:
Prof Pavel Chigansky
Ms. rachel buchuk
Course/Module description:
Everything: Sufficient statistics, and the factorization criterion. Sufficiency and minimal sufficiency. The likelihood function and identifiablity. Estimation. The quadratic loss function and comparison of estimator. The Rao-Blackwell improvement. Complete statistics and the Lehmann-Schaffe Theorem. The Fisher information and the information inequality. The asymptotics of the MLE. Confidence intervals and statistical tests of hypotheses. The classical CI's in the Gaussian model. The Neyman-Pearson lemma, UMP tests, GLT, Wilk's, Wald's tests. Bayesian statistics, including estimation, tests,, and CI (if only there were ones), including conjugate families. Nonparametric statistics. Permutation, Wilcoxon sign, Wilcoxon rank tests. Asymptotic relative efficiency, empirical distribution function. Kolomogorov-Smirnov tests. Introduction to nonparametric estimation of the density fucntion.
Course/Module aims:
Theoretical understanding of the statistical tool box.
Learning outcomes - On successful completion of this module, students should be able to:
1. To understand the theoretical justification of statistics.
2. To understand the mathematical foundation of statistics.
3. To understand the basic definitions.
Attendance requirements(%):
0%
Teaching arrangement and method of instruction:
Lectures and exercises.
Course/Module Content:
See above.
Required Reading:
N-A
Additional Reading Material:
Lecture notes will be distributed during the course. Additional recommended reading:
Felix Abramovich and Ya'acov Ritov: Statistical Theory: A Concise Introduction
P.Bickel, K.Doksum, Mathematical Statistics: basic ideas and selected topics, 1977
Casella, George; Berger, Roger L. Statistical inference, 1990.
Course/Module evaluation:
End of year written/oral examination 80 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 0 %
Assignments 0 %
Reports 0 %
Research project 0 %
Quizzes 20 %
Other 0 %
Additional information:
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