Reasoning with data

What it covers

This unit provides a foundational introduction to data science, covering core concepts, methods, and tools used to collect, analyse, model, and interpret data. You will develop practical skills in using programming languages such as Python and/or R for data science tasks, including data handling, visualization, and descriptive statistical analysis. The unit introduces principles of sampling, probability, expectation, and basic probability models, providing a basis for reasoning about uncertainty and variation in data. You will explore predictive modelling methods, including linear models, and examine how models can be fitted and evaluated using approaches such as maximum likelihood and minimum loss. The unit also introduces key ideas in statistical inference, including confidence intervals and hypothesis testing. In addition, you will consider ethical and privacy issues that arise when working with data. By the end of the unit, you will be able to apply foundational data science techniques, interpret statistical results, and communicate data-driven insights clearly and responsibly.

Assessment

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