BIOSTATS 6003EX - Probability and Distribution Theory

External - Semester 2 - 2016

The course information on this page is being finalised for 2016. Please check again before classes commence.

This course will focus on applying the calculus-based techniques learned in Mathematical Background for Biostatistics to the study of probability and statistical distributions. These two courses, together with the subsequent Principles of Statistical Inference course, will provide the core prerequisite mathematical statistics background required for the study of later courses in the Graduate Diploma or Masters degree. This course begins with the study of probability, random variables, discrete and continuous distributions, and the use of calculus to obtain expressions for parameters of these distributions such as the mean and variance. Joint distributions for multiple random variables are introduced together with the important concepts of independence, correlation and covariance, marginal and conditional distributions. Techniques for determining distributions of transformations of random variables are discussed. The concept of the sampling distribution and standard error of an estimator of a parameter is presented, together with key properties of estimators. Large sample results concerning the properties of estimators are presented with emphasis on the central role of the normal distribution in these results. General approaches to obtaining estimators of parameters are introduced. Numerical simulation and graphing with Stata is used throughout to demonstrate concepts.

• General Course Information
Course Details
Course Code BIOSTATS 6003EX Probability and Distribution Theory Public Health Semester 2 Postgraduate Coursework External 3 Up to 12 hours per week for 13 weeks N BIOSTATS 6001EX Available to Grad Cert, Grad Dip, M Biostatistics students only This course will focus on applying the calculus-based techniques learned in Mathematical Background for Biostatistics to the study of probability and statistical distributions. These two courses, together with the subsequent Principles of Statistical Inference course, will provide the core prerequisite mathematical statistics background required for the study of later courses in the Graduate Diploma or Masters degree. This course begins with the study of probability, random variables, discrete and continuous distributions, and the use of calculus to obtain expressions for parameters of these distributions such as the mean and variance. Joint distributions for multiple random variables are introduced together with the important concepts of independence, correlation and covariance, marginal and conditional distributions. Techniques for determining distributions of transformations of random variables are discussed. The concept of the sampling distribution and standard error of an estimator of a parameter is presented, together with key properties of estimators. Large sample results concerning the properties of estimators are presented with emphasis on the central role of the normal distribution in these results. General approaches to obtaining estimators of parameters are introduced. Numerical simulation and graphing with Stata is used throughout to demonstrate concepts.
Course Staff

Course Coordinator: Dr Amy Salter

Course Coordinator : Dr Amy Salter
Phone: +61 8313 4619
Location: Level 11, 178 North Terrace
Course Timetable

The full timetable of all activities for this course can be accessed from Course Planner.

• Learning Outcomes
Course Learning Outcomes

No information currently available.

• Learning Resources
Online Learning
• Learning & Teaching Activities
Learning & Teaching Modes

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

Small Group Discovery Experience
• Assessment

The University's policy on Assessment for Coursework Programs is based on the following four principles:

1. Assessment must encourage and reinforce learning.
2. Assessment must enable robust and fair judgements about student performance.
3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
4. Assessment must maintain academic standards.

Submission

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
FNS   Fail No Submission
F 1-49 Fail
P 50-64 Pass
C 65-74 Credit
D 75-84 Distinction
HD 85-100 High Distinction
CN   Continuing
NFE   No Formal Examination
RP   Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through Access Adelaide.

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