ANALYSES OF LINEAR MODELS
Credit points: 15
Modern research often involves the analysis of data for more than one variable and in this regard, linear models are the most widely used class of models. They relate a reponse variable to one or more explanatory variables enabling researchers to answer important research questions as well as make future predictions. The methods are used in many areas including biological science, economics, engineering, medical science and psychological science. Topics include simple and multiple linear regression, response and explanatory variable transformations, ANOVA and ANCOVA, as well as more modern methodologies such as generalized linear models and linear mixed effects models. This subject has a stong emphasis on preparing students for future careers in statistics.
FacultyFaculty of Science, Tech & Engineering
Subject Co-ordinatorAgus Salim
Available to Study Abroad StudentsYes
Subject year levelYear Level 3 - UG
Prerequisites ONE OF STA2ABS or STA2AMS or STA2MD
Incompatible subjects STA4LM
|Resource Type||Title||Resource Requirement||Author and Year||Publisher|
|Readings||Introduction to Linear Regression Analysis||Recommended||Montgomery, DC, Peck, EA and Vining, G 2006||WILEY, 4TH EDITION.|
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Melbourne, 2014, Semester 2, Day
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorAgus Salim
One 1.0 hours computer laboratory per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
Two 1.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
One 1.0 hours practical per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
|2 Assignments (approx. 800 words each)||20|
|2-hour short answer Final Examination||50|
|5-minute oral presentation briefly describing an applied research paper.||5|
|5-minute oral presentation of a current job ad||Hurdle Speaking preparation/practice||0|