Units:

6

Description:

This course will provide the expertise and skills for undertaking a range of practical applications such as descriptive statistics, exploratory data analysis and business intelligence. This will involve the process of collecting, cleaning, interpreting, transforming, exploring, analysing and modeling data with the goal of discovering useful information, communicating insights and supporting decision-making. Statistical hypothesis testing will be presented as a means of quantifying the confidence that can be assigned to the outcome of empirical investigations. The advantages of using visualization techniques to facilitate a better understanding of the data and to enable communication of the outcomes will be emphasised throughout. Participants will obtain hands-on experience during project assignments that utilize publicly available datasets.

Prerequisites: Background in quantitative discipline (Engineering, Computer Science, Physics, Mathematics, Statistics); Programming.

Last Modified: 2018-11-09 2:55PM

Semesters offered:

• Spring 2015