sta3lm analyses of linear models
ANALYSES OF LINEAR MODELS
STA3LM
2020
Credit points: 15
Subject outline
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. Linear models relate a response variable to one or more explanatory variables enabling researchers to answer important research questions and make predictions about how variables will respond. These methods are used in many areas including biological science, economics, engineering, medical science and psychological science. Topics covered in this subject 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 strong emphasis on preparing students for future careers in statistics. This subject addresses La Trobe's Innovation and Entrepreneurship Essential which entails developing the ability to tackle problems creatively, generating new ideas, taking calculated risks and creating change to achieve ambitions now and in the future.
SchoolEngineering and Mathematical Sciences (Pre 2022)
Credit points15
Subject Co-ordinatorAmanda Shaker
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 3 - UG
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectYes
Subject particulars
Subject rules
Prerequisites Must pass one of the following: STA2ASM or STA2ABS or STA2AMS or STA2MD or STM2PM
Co-requisitesN/A
Incompatible subjectsSTA4LM
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Introduction to Linear Regression Analysis
Resource TypeBook
Resource RequirementRecommended
AuthorMontgomery, DC, Peck, EA and Vining, G
Year2006
Edition/Volume4TH EDITION
PublisherWILEY
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
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Melbourne (Bundoora), 2020, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorAmanda Shaker
Class requirements
Computer LaboratoryWeek: 32 - 43
One 1.00 hour computer laboratory per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
LectureWeek: 31 - 43
Two 1.00 hour lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
PracticalWeek: 32 - 43
One 1.00 hour practical per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
2 Assignments (equivalent to 1000 words) | N/A | N/A | No | 20 | SILO1, SILO2, SILO3, SILO4 |
2-hour short answer Final Examination (2000 word equiv) | N/A | N/A | No | 50 | SILO1, SILO2, SILO3, SILO4 |
Two 5-minute oral presentations (500 word equivalent)Hurdle: satisfactory oral presentations must be given | N/A | N/A | Yes | 5 | SILO4 |
Consulting role-play (1000 word equiv.) | N/A | N/A | No | 25 | SILO2, SILO3, SILO4, SILO5 |