ADVANCED TOPICS IN STATISTICS D

STA5ATD

2020

Credit points: 15

Subject outline

This subject enables 5th year statistics students to enrol in subjects offered through the Key Centre of Statistical Science (KCSS) or through the Department of Mathematics and Statistics Access Grid Room. Subject syllabus is dependent on the subject chosen and students are advised to refer to the departmental website or the Department of Mathematics and Statistics Master of Statistical Science Coordinator prior to enrolment for more details. Enrolment into this subject must be approved by the Department of Mathematics and Statistics Master of Statistical Science Coordinator.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorAndriy Olenko

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

Prerequisites only by approval of the Master of Statistical Science coordinator

Co-requisitesN/A

Incompatible subjectsSTA4ATD

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Introduction to Linear Regression Analysis

Resource TypeRecommended

Resource RequirementN/A

AuthorMontgomery, D. C, Peck, E. A. 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

01. Demonstrate specialised theoretical and technical skills in a specified statistics topic.
02. Use specialised cognitive and technical skills to critically analyse, reflect on and synthesise complex information, problems, concepts and theories relevant to the topic.
03. Apply established theories relevant to the topic.
04. Use advanced communication skills to transmit knowledge and ideas of statistics to others.
05. Demonstrate autonomy, expert judgement, adaptability and responsibility as a statistician.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2020, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorAndriy Olenko

Class requirements

Lecture Week: 10 - 22
Two 1.00 h lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
This is dependent on the subject.N/AN/AN/ANo100 SILO1, SILO2, SILO3, SILO4, SILO5

Melbourne (Bundoora), 2020, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorAndriy Olenko

Class requirements

Lecture Week: 31 - 43
Two 1.00 h lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
This is dependent on the subject.N/AN/AN/ANo100 SILO1, SILO2, SILO3, SILO4, SILO5