​CSS3232 – Statistics

Course Description

To provide the students the knowledge of concepts and theories of statistics that is highly used in machine learning and data mining, so that the students are able to apply the statistical theories into the algorithms. ​This course provides the students the knowledge of concepts and theories of statistics such as probability, correlation and regression, that is highly used in machine learning and data mining, so that the students are able to apply the statistical theories into the algorithms.

​​Content Outline of the Course/Module:

  • Introduction to Statistics
  • Summarising and Graphing Data
  • Statistics for Describing, Exploring, Data
  • Probability
  • Normal Probability Distributions
  • Estimates and Sample Sizes
  • Hypothesis Testing
  • Inferences from Two Samples
  • Correlation and Regression

Course Outcome

Upon completion of this course, students should be able to:

  • Apply and practice using statistical techniques to analyse the real-life data.
  • Construct simple models to solve real-life problems.
  • Explain how the problems can be solved by using statistical techniques.

Subject Area

Core

Course Director

Yiiong Siew Ping

​​​​Teaching-learning Methods Assessment Methods
Lecture ​Assignment, Progress Test, Final Examination
Tutorial ​Assignment, Progress Test, Final Examination
​Assignment ​Assignment