Handbook

There is a more recent version of this academic item available.

Overview

Regression is a set of statistical techniques widely used to analyse relationships between several variables. In this course, students will
explore the applications of a range of regression techniques, including: linear regression; analysis of variance (ANOVA) and analysis of covariance (ANCOVA); generalised linear and generalised additive models; generalised local likelihood; Poisson, logistic and log-linear regression models; penalised regression methods; testing GLMs and diagnostics; variable selection and cross-validation; splines, penalised splines, thin plate splines and multidimensional splines; smoothing splines and regression splines and kernel smoothing.

The lectures will be complemented with worked examples using the R data analysis and statistical programming software.
This online course covers the same topics as in MATH5806 and is only available to students enrolled in the online Diploma of Data Science and the online Master of Data Science.

Conditions for Enrolment

Prerequisite: Must be enrolled in 5646 or 8646 and have completed ZZSC9001 Foundations of Data Science and ZZSC5905 Statistical Inference for data scientists or equivalent

Exclusion Courses

Delivery

Fully online - Intensive

Please note that the above delivery information is an indication on how this course may be delivered within the year. Delivery mode(s) for each term can be viewed on other sources such as myUNSW and class timetable site.

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Fees

Type	Amount
Commonwealth Supported Students (if applicable)	$556
Domestic Students	$4800
International Students	$4800

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Commonwealth Supported Students:

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Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

Faculty
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School
School: The academic unit responsible for teaching in disciplines or subject areas (school is part of a faculty).

Study Level
Study Level refers to the academic level of a program, specialisation or course.

Postgraduate

Offering Terms
Depending on the Academic Calendar type, an offering term generally refers to an academic teaching period of between 8-13 weeks in duration.

Hexamester 1, Hexamester 4

Campus

Sydney

Academic Calendar

Hexamester

Field of Education

010103 Statistics

Timetable

Course Outline
This link will take you to UNSW Course Outline website that is first released for all faculties for 2024 academic year. Note that the Handbook publishes course information regardless of whether the course is offered (and therefore has a course outline available), or not.

Regression Analysis for Data Scientists

ZZSC5806

6 Units of Credit