MODELS FOR DATA ANALYSIS

STA2MD

2014

Credit points: 15

Subject outline

The analysis of scientific, engineering and economic data makes extensive use of probability models. This subject describes the most basic of these models and their properties. Specific topics covered in this subject include a wide range of discrete and continuous univariate distributions; joint distributions; conditional expectation; mean and variance of linear combinations of random variables; Chebyshev's inequality; moment generating functions; the law of large numbers; the Central Limit Theorem. To help students with little or no previous knowledge in calculus one lecture per week consists of "calculus for statistics".

FacultyFaculty of Science, Tech & Engineering

Credit points15

Subject Co-ordinatorKatherine Seaton

Available to Study Abroad StudentsYes

Subject year levelYear Level 2 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites For student enrolled in course SVCSE or SHCSY: MAT1CPE or MAT1NLA. For all other students: STA1SS or STA1LS or STA1PSY or ECO1ISB or MAT1CDE or MAT1CLA.

Co-requisitesN/A

Incompatible subjects STA2MDA

Equivalent subjectsN/A

Special conditionsN/A

Subject options

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Start date between: and    Key dates

Melbourne, 2014, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorKatherine Seaton

Class requirements

Practical Week: 31 - 43
One 1.0 hours practical per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Lecture Week: 31 - 43
Three 1.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementComments%
One 2.5-hour examination80
Ten assignments (2-3 pages each)20