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.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Amanda Shaker
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 3 - UG
Available as Elective: No
Learning Activities: N/A
Capstone subject: Yes
Subject particulars
Subject rules
Prerequisites: Must pass one of the following: STA2ASM or STA2ABS or STA2AMS or STA2MD or STM2PM
Co-requisites: N/A
Incompatible subjects: STA4LM
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Introduction to Linear Regression Analysis
Resource Type: Book
Resource Requirement: Recommended
Author: Montgomery, DC, Peck, EA and Vining, G
Year: 2006
Edition/Volume: 4TH EDITION
Publisher: WILEY
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 2, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Amanda 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 |