What you will learn

• Evaluate and interpret complex data sets with probabilistic models, applying Bayes’ theorem and Chebyshev’s inequality to solve real-world problems.

• Design hypothesis tests, including t-tests, z-tests, and chi-square tests, to validate data-driven hypotheses in various professional contexts.

• Construct and optimise predictive models using multiple and nonlinear regression techniques to forecast outcomes and improve decision-making.

• Synthesise probability and statistical knowledge to develop innovative solutions for complex analytical challenges.