Special Math Lecture： Statistics

Objective of the Course (as Course Overview)

Statistics deals with the collection, the analysis, the interpretation and the representation of data, always with the notion of uncertainty in the background. It plays a central role in many scientific investigations, and it is one of the most popular mathematical tools used in the industry. During this one semester course, the basic notions of statistics will be introduced. Depending on the interest of the audience, various concrete applications will be further developed.

Course Prerequisites

Basic knowledge on calculus and linear algebra, as provided in Calculus I & II and in Linear algebra I & II. Some knowledge on probability as available on

http://www.math.nagoya-u.ac.jp/~richard/lecturefall2017.html

would also be useful, but the necessary material will be briefly reviewed at the beginning of the course. Motivated 1st year students can also attend without these prerequisites but after a discussion with the instructor.

Program

I) Probability theory
II) Random sample
III) Data reduction
IV) Point estimation
V) Hypothesis testing
VI) Interval estimation
VII) Asymptotic evaluations
VIII) Analysis of variance and regression
IX) Regression models
X) The application of tree-based methods for the analysis of MathSciNet database: : Lecture presented by Qiwen Sun

Evaluation Methods

The final grade will be based on the active participation during the lectures and on some written reports.

Notice for Students

This course in an optional subject which does not count towards the number of credits required for graduation in any program at Nagoya University.

Textbook

Material will be provided during the lectures.

Reference Book

Reference books will be provided during the lectures

The lecture notes

http://www.math.nagoya-u.ac.jp/~richard/teaching/s2019/Statistics.pdf

Appendix

Appendix

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