Note: This is an archived Handbook entry from 2016.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2016:Semester 2, Parkville - Taught on campus.
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
Study Period Commencement:
|Recommended Background Knowledge:|| |
|Non Allowed Subjects:|| |
Passing this subject (MAST20005 Statistics) precludes subsequent credit for either of
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.
CoordinatorDr Davide Ferrari
Second Year Coordinator
This subject introduces the theory underlying modern statistical inference and statistical computation. In particular, it demonstrates that many commonly used statistical procedures arise as applications of a common theory. Both classical and Bayesian statistical methods are developed. Basic statistical concepts including maximum likelihood, sufficiency, unbiased estimation, confidence intervals, hypothesis testing and significance levels are discussed. Applications include distribution free methods, goodness of fit tests, correlation and regression; the analysis of one-way and two-way classifications.
Students completing this subject should
Three written assignments due at regular intervals during semester amounting to a total of up to 50 pages (20%), a 45-minute computer laboratory test held at the end of semester (10%), and a 3-hour written examination in the examination period (70%).
|Prescribed Texts:|| |
R. Hogg, E. Tanis, and D. Zimmerman, Probability and Statistical Inference. 9th Edition, Pearson, 2015.
|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|
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
This subject is available for science credit to students enrolled in the BSc (both pre-2008 and new degrees), BASc or a combined BSc course.
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 and R in the subject.
Environmental Science major |
Environments Discipline subjects
Science-credited subjects - new generation B-SCI and B-ENG.
Selective subjects for B-BMED
Statistics / Stochastic Processes
Statistics / Stochastic Processes
|Related Breadth Track(s):||
Mathematics for Economics |
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