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Unit (2019)

Information on this page, including unit offerings, is from the 2019 academic year.

Applied Statistics (MAS223)

Organisational Unit Information Technology, Mathematics and Statistics
Credit Points 3
Availability MURDOCH: S2-internal, S2-external
Teaching Timetables Murdoch S2
Description This unit considers select topics from experimental design and survey methods, descriptive statistics, hypothesis testing and modelling for continuous and categorical variables. Throughout, advanced statistical software will play an important role in data visualisation and analysis. Students will consider topics through the presentation of real research problems from a number of disciplines, gaining valuable experience in the application of statistics in a variety of contexts, including a project simulating statistical problems commonly encountered in the workplace.
Unit Learning Outcomes On successful completion of the unit students should be able to:
1. Carry out a variety of statistical analyses using statistical software. In particular, students should be able to:
a. analyse data using linear regression,
b. apply the bootstrap for variance estimation,
c. assess predictive performance for a model using the bootstrap and cross-validation,
d. utilise principal components analysis as a means of dimension reduction,
e. use discriminant analysis for classification, and
f. be familiar with a variety of other statistical methods.
2. Explain conceptually the various statistical methods covered in the unit, the correct application of these methods, and interpret statistical software output.
3. Write a technical report of findings based on statistical analyses.
Timetabled Learning Activities Lectures: 3 x 1 hour per week; tutorials: 1 x 1 hour per week; workshops: 1 x 2 hours per week (Weeks 1-3).
Unit Learning Experiences This unit uses a mixture of structured activities and assessments to assist students in learning the material covered in the unit. Structured activities include lectures and tutorials, and assessments include assignments, a project, and a final exam.
It is essential for internal students to attend the tutorials in this unit.
Assessment All students' abilities to correctly apply statistical methods will be assessed at regular intervals during the semester via assignments and a project. These assessments are designed to allow students to demonstrate their ability in each of the content areas of the unit and to give them regular feedback on your their progress, helping them to identify their areas of strength or weakness during the semester. Assignment solutions and results will be posted progressively on the Learning Management System.
The weightings for assessment items are as follows:
Assignments (3) - 30%
Project - 15%
Final Examination - 55%
Prerequisites MAS183 Statistical Data Analysis.
Previously 2014: 'Applied Statistics and Process Management'
Appears in these Courses/Majors:
see individual structures for context
Advanced Mathematics Major Teaching Area (BEd(Sec)) [New in 2019]
Animal Health (BSc) [New in 2015]
Animal Science (BSc) [New in 2014]
Biological Sciences (BSc) [New in 2014]
Biomedical Science (BSc) [New in 2014]
Chemistry (BSc) [New in 2014]
Clinical Laboratory Science (BSc) [New in 2015]
Conservation and Wildlife Biology (BSc) [New in 2014]
Criminology + Forensic Biology and Toxicology [Combined] (BCrim)+(BSc)
Crop and Pasture Science (BSc) [New in 2016]
Engineering Technology (BSc) [New in 2014]
Environmental Management and Sustainability (BSc) [New in 2014]
Environmental Science (BSc) [New in 2014]
Forensic Biology and Toxicology (BSc) [New in 2014]
Genetics and Molecular Biology (BSc) [New in 2014]
Laboratory Medicine (BSc/BLabMed) [New in 2016]
Marine Biology (BSc) [New in 2017]
Marine Science (BSc) [New in 2014]
Mathematics and Statistics (BSc) [New in 2014]
Mathematics Major Teaching Area (BEd(Sec)) [New in 2019]
Mineral Science (BSc) [New in 2014]
Physics and Nanotechnology (BSc) [New in 2014]
Sport and Health Science (BSc) [New in 2014]
Appears in these Minors Applied Statistics
Fisheries Science
Internet Access RequirementsMurdoch units normally include an online component comprising materials, discussions, lecture recordings and assessment activities. All students, regardless of their location or mode of study, need to have access to and be able to use computing devices with browsing capability and a connection to the Internet via Broadband (Cable, ADSL or Mobile) or Wireless. The Internet connection should be readily available and allow large amounts of data to be streamed or downloaded (approximately 100MB per lecture recording). Students also need to be able to enter into online discussions and submit assignments online.

Contacts

Unit Coordinator
MAS223
Associate Professor Nicola Armstrong
Associate Professor

Murdoch Campus
t: 9360 2480
e: N.Armstrong@murdoch.edu.au
o: 245.3.036 - Science and Computing, Murdoch Campus
Unit Contacts
MAS223

MURDOCH: S2-External
MURDOCH: S2-Internal
Associate Professor Nicola Armstrong
Associate Professor

Murdoch Campus
t: 9360 2480
e: N.Armstrong@murdoch.edu.au
o: 245.3.036 - Science and Computing, Murdoch Campus
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