MAST20006 Probability for Statistics
Credit Points:  12.5  

Level:  2 (Undergraduate)  
Dates & Locations:  This subject has the following teaching availabilities in 2017: Semester 1, Parkville  Taught on campus.Show/hide details
Timetable can be viewed here. For information about these dates, click here.  
Time Commitment:  Contact Hours: 3 x one hour lectures per week, 1 x one hour practice class per week, and 1 x one hour computer laboratory class per week Total Time Commitment: Estimated total time commitment of 170 hours  
Prerequisites:  One of
Subject Study Period Commencement: Credit Points: and one of Subject Study Period Commencement: Credit Points: MAST10013 UMEP Maths for High Achieving Students  
Corequisites:  None  
Recommended Background Knowledge:  None  
Non Allowed Subjects:  Students may only gain credit for one of
 
Core Participation Requirements:  For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry. It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability 
Subject Overview:  This subject develops the probability theory that is necessary to understand statistical inference. Properties of probability are reviewed, random variables are introduced, and their properties are developed and illustrated through common univariate probability models. Models for the joint behaviour of random variables are introduced, along with conditional probability and Markov chains. Methods for obtaining the distributions of functions of random variables are considered along with techniques to obtain the exact and approximate distributions of sums of random variables. These methods will be illustrated through some well known normal approximations to discrete distributions and by obtaining the exact and approximate distributions of some commonly used statistics. Computer packages are used for numerical and theoretical calculations but no programming skills are required. 

Learning Outcomes:  At the completion of the subject, students are expected to:

Assessment: 
Five written assignments due at regular intervals during semester amounting to a total of up to 50 pages (20%), a 45minute computer laboratory test held at the end of semester (10%), and a 3hour written examination in the examination period (70%).

Prescribed Texts:  Hogg and Tanis, Probability and Statistical Inference. 8th Edition, Prentice Hall, 2010. 
Breadth Options:  This subject potentially can be taken as a breadth subject component for the following courses: You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects. 
Fees Information:  Subject EFTSL, Level, Discipline & Census Date 
Generic Skills:  In addition to learning specific skills that will assist students in their future careers in science, they should progressively acquire generic skills from this subject that will assist them in any future career path. These include

Notes:  This subject is available for science credit to students enrolled in the BSc (both pre2008 and new degrees), BASc or a combined BSc course. Students undertaking Actuarial Studies should take MAST20004 Probability instead of MAST20006 Probability for Statistics. Students undertaking this subject are required to regularly use computers with the computer algebra system Maple and statistics package R installed. Students undertaking this subject are not assumed to have any special computer skills at the beginning. They will learn the basic skills of using Maple in the subject. 
Applied Mathematics Applied Mathematics Discrete Mathematics / Operations Research Discrete Mathematics / Operations Research Environmental Science major Environments Discipline subjects Sciencecredited subjects  new generation BSCI and BENG. Selective subjects for BBMED Statistics / Stochastic Processes Statistics / Stochastic Processes  
Mathematics and Statistics Mathematics for Economics Accelerated Mathematics 