Academics
-
Schools
- School of Law
- School of Business Administration
- School of Accounting
- School of Finance
- School of Economics
- School of Public Finance and Taxation
- School of Humanities and Communication
- School of Information Science
- School of Public Administration
- School of Art and Design
- School of Foreign Studies
- School of Geography and Tourism
- School of Statistics and Mathematics
- School of Greater Bay Area Film and Television Industry
- International School
- International Business School
- Cultural Creativity and Tourism School
- School of Digital Economy
- Undergraduate Education
- Postgraduate Education
Modern Non-parametric Statistics
Release Date: 2017-09-221.Basic Course Information
Course Title:Modern Non-parametric Statistics
Course Code:
Credit Hours/Credits:
Students:Undergraduate Students who major in Statistics and Applied Statistics
Prerequisites:
Subsequent Course(s):None
Course Category: Professional Optional Course(for Statistics) and Professional Foundamental Course(for Applied Statistics).
Assessment: Final exam (70%) + Participation & Assignments (30%)
2. Course Introduction
This course is a basic course designed to teach non parametric statistics and help students understand the frontier of statistics. The aim is to make the students realize that nonparametric statistical method is one of the most commonly used inference methods in statistics, and it can be used to understand the basic concepts of nonparametric statistical methods, as well as to grasp the basic methods of nonparametric statistics.
The content includes: special methods and applied conditions in researching unknown distributions, basic distributions, permissible limits, asymptotic efficiency, distribution rank tests and randomization tests.