BIOS6050

Principles of Statistical Inference

10 Units

Introduces the core concepts of statistical inference, including estimators, confidence intervals, Type I & II errors and p-values. The emphasis is on the practical interpretation of these concepts in biostatistical contexts, including an emphasis on the difference between statistical and practical significance. This course is offered in conjunction with the Biostatistics Collaboration of Australia (BCA)

Faculty Faculty of Health and Medicine
School School of Medicine and Public Health
Availability Semester 1 - 2014 (Distance Education - Callaghan)
Semester 2 - 2014 (Distance Education - Callaghan)
Semester 1 - 2015 (Distance Education - Callaghan)
Semester 2 - 2015 (Distance Education - Callaghan)
Objectives

At the completion of this course the student will:

  1. Have a deeper understanding of fundamental concepts in statistical inference and their practical interpretation and importance in biostatistical contexts
  2. Understand the theoretical basis for frequentist and Bayesian approaches to statistical inference 3, Be able to apply likelihood-based methods of inference, with particular reference to problems of relevance in biostatistical contexts.
Content

The course begins by introducing core concepts of statistical inference, including estimators, confidence intervals, Type I&II errors, and p-values. Concepts in classical estimation theory, including bias and efficiency are discussed. The course will then move on to a general study of the likelihood function, which will be used as a basis for the study of likelihood based methodology, including maximum likelihood estimation and inference based on likelihood ratio, Wald and score test procedures. The Bayesian approach to statistical inference will be studied and contrasted with the classical frequentist approach. Additional areas of study will include nonparametric procedures, exact inference and resampling based methodology.

Replacing Course(s) N/A
Transition N/A
Industrial Experience 0
Assumed Knowledge Mathematical Background for Biostatistics (BIOS6040); Probability and Distribution Theory (BIOS6170).
Modes of Delivery Distance Learning : Paper Based
Teaching Methods Self Directed Learning
Assessment Items
  • Essays / Written Assignments - Assignments.
Contact Hours
  • Self Directed Learning: for 6 hour(s) per Week for Full Term
Compulsory Components
  • Requisite by Enrolment: This course is only available to students enrolled in the Graduate Diploma in Medical Statistics or Master of Medical Statistics programs.
Course Materials None listed
Timetable 2015 Course Timetables for BIOS6050

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