Statistical Modelling and Experimental Design

• • Topics will be available to enrolled students in the subjects Learning Management System site approximately one week prior to the commencement of the teaching period.

You must have successfully completed the following subject(s) before starting this subject:

UNE-SCI210-Introduction to Scientific Programming , or UNE-STAT100-Introduction to Statistical Modelling

Special requirements

• EquipmentDetails - Headphones or speakers (required to listen to lectures and other media) Headset, including microphone (highly recommended) Webcam (may be required for participation in virtual classrooms and/or media presentations).
• SoftwareDetails - Please refer students to link for requirements: http://www.une.edu.au/current-students/support/it-services/hardware It is essential for students to have reliable internet access in order to participate in and complete your units, regardless of whether they contain an on campus attendance or intensive school component.
• TravelDetails - Travel may be required to attend the Final Examination for this subject.
• OtherDetails -

  Textbook information is not available until approximately 8 weeks prior to the commencement of the Teaching period.

  Students are expected to purchase prescribed material.

  Textbook requirements may vary from one teaching period to the next.

Regression models are the foundation of many statistical models and experimental designs. In this unit, students learn to develop and analyse linear and logistic regression-based statistical models, and are taught important experimental designs used by many fields. This unit is appropriate for students in the natural or social sciences interested in developing and applying statistical models in their fields, as well as for students in the computational and mathematical sciences interested in learning about applied statistics.

Topics include: design and analysis of experiments with one or two factors; orthogonal partitions; block designs; multiple regression, including use of indicator variables; and an introduction to logistic regression. Students undertaking this subject at postgraduate level will also be required to complete an advanced special reading topic.

Assessment 1: Online Quiz: Simple Linear Regression and hypothesis testing. Students must obtain at least 40% for the assessments overall. Relates to Learning Outcomes 1, 3. Assessment 2: Multiple Regression. Students must obtain at least 40% for the assessments overall. Relates to Learning Outcomes 1, 2, 3. Assessment 3: Model Building, Variable Screening and Residual Analysis. Students must obtain at least 40% for the assessments overall. Relates to Learning Outcomes 1, 2, 3. Assessment 4: Generalised Linear Models. Students must obtain at least 40% for the assessments overall. Relates to Learning Outcomes 1, 2, 3. Assessment 5: Experimental Design, Multi-factor Designs and Contrasts. Students must obtain at least 40% overall. Relates to Learning Outcomes 1, 2, 3. Final Examination: 2 hrs 15 mins. Notes - Must obtain at least 40% in the final examination and obtain an overall passing grade. Relates to Learning Outcomes 1, 2, 3. UNE manages supervised exams associated with your UNE subjects. Prior to census date, UNE releases exam timetables. They’ll email important exam information directly to your UNE email address.

• Assessment 1 (2.5%)
• Assessment 2 (10%)
• Assessment 3 (12.5%)
• Assessment 4 (12.5%)
• Assessment 5 (12.5%)
• Final Examination (50%)