STAT40330 Nonparametric Statistics

Academic Year 2018/2019

The course covers both theory and practical applications of nonparametric methods. It serves to reinforce and provide a contrast to classical statistical methods. Topics covered include: distribution-free statistics, statistics utilizing counting and ranking, permutation tests. Modern methods of jackknife, bootstrap, density estimation and non parametric regression and smoothing will be covered. The statistical software packages Minitab and R will be used. Typewritten notes for the course will be provided on Blackboard. The lectures will be shared with final year undergraduates but there will be a different exam and more reading and different assignments will be required than STAT40080

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module students should be able to demonstrate familiarity with standard nonparametric methods. They should be able to carry out these procedures on data sets using the statistical software packages Minitab and R. They should be able to understand the difference between nonparametric methods and classical methods and have the knowledge to make informed judgements as to what method is appropriate in a given problem.

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Specified Learning Activities

36
Autonomous Student Learning

90
Total

150
 
Requirements, Exclusions and Recommendations
Learning Requirements:

A first course in Statistics, including graphical and numerical summaries of data, hypothesis testing, confidence intervals, ANOVA, regression and correlation, comparing two binomial proportions.



Module Requisites and Incompatibles
Incompatibles:
Nonparametric Statistics (STAT40080)

 
Description % of Final Grade Timing
Examination: End of semester exam

80

 2 hour End of Trimester Exam
Continuous Assessment: Homework assignments

20

 Throughout the Trimester

Compensation

This module is not passable by compensation

Resit Opportunities

End of Semester Exam

Remediation

If you fail this module you may do a resit exam