Statistics for Data Science

Postgraduate | 2026

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Area/Catalogue
MATH 5029
Course ID icon
Course ID
207597
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course level icon
Course level
5
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

Course overview

This course will provide a solid foundation in statistical theory, and applications of statistical methods in solving complex problems. Content includes: Exploratory Data Analysis, sampling, estimation, hypothesis testing; Statistical models: correlation analysis, linear regression, logistic regression; Experimental Design and hypothesis testing methods: ANOVA, chi-square test, non-parametric methods, and multivariate extensions; Introduction to machine learning; Using SAS to solve statistical problems.

Course learning outcomes

  • Understand the foundational theory of statistics.
  • Understand and demonstrate proficiency in statistical analysis of data.
  • Apply statistical methods to solve real-world problems and communicate these solutions effectively.
  • Demonstrate proficiency in using SAS for data exploration and statistical analysis tasks.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A