REGRESSION ANALYSIS

STA4RA

2017

Credit points: 15

Subject outline

The main objective of this unit is to provide an introduction to the theory of regression analysis. The topics for this unit include; multiple linear regression; classical estimation and testing; residual analysis; diagnostics; robust regression and modern dimension reduction. This unit considers both theoretical derivations and practical applications through the use of the freely available statistics software package R (see http://www.r-project.org/). Previous knowledge of R is not required.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorLuke Prendergast

Available to Study Abroad StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites STA3LM and STA3AS

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjects STA41RA

Special conditionsN/A

Graduate capabilities & intended learning outcomes

01. Demonstrate advanced theoretical and technical knowledge in regression analysis.

Activities:
Discussed and demonstrated in lectures. Proofs derived by students in practice classes. Assignment questions, with feedback.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Personal and Professional Skills (Autonomy and independence)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

02. Use advanced cognitive and technical skills to select and apply methods to critically analyse, evaluate and interpret output from various regression methodologies.

Activities:
Discussed and demonstrated in lectures. Analyses interpreted and critiqued by students in practice classes. Assignment questions, with feedback.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Personal and Professional Skills (Autonomy and independence)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

03. Use advanced cognitive and technical skills to analyse, generate and transmit solutions to complex data sets suitable for linear models.

Activities:
Discussed and demonstrated in lectures. Analyses communicated by students in practice classes. Assignment questions, with feedback.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Personal and Professional Skills (Autonomy and independence)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

04. Use advanced communication skills to transmit knowledge and ideas of statistics to others.

Activities:
Discussed and demonstrated in lectures. Students discuss results with class mates and lecturer in practice classes. Assignment questions, with feedback.
Related graduate capabilities and elements:
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Personal and Professional Skills (Autonomy and independence)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

05. Demonstrate autonomy, well-developed judgement, adaptability and responsibility as a statistician.

Activities:
Discussed and demonstrated in lectures. Interpretations of results, including transparency of methods, carried out in class. Assignment questions, with feedback.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Personal and Professional Skills (Autonomy and independence)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

Subject options

Select to view your study options…

Start date between: and    Key dates

Melbourne, 2017, Semester 1, Day

Overview

Online enrolmentNo

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorLuke Prendergast

Class requirements

Lecture/Practical Week: 10 - 22
One 2.0 hours lecture/practical per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
one 2-hour examination.70 01, 02, 03, 05
three assignments30 01, 02, 03, 04, 05