This module introduces the fundamental concepts of probability, data analysis, and statistics. Underlying statistical theory is the assumption that data sets are samples following a probability distribution describing their behaviour. An introduction to probability theory including conditional probability and Bayes' Theorem, and discrete and continuous random variables is given. Subsequently the module introduces the foundational concepts of data analysis and the application of statistical packages. Students will engage in activities involving data sampling and exploration and provide an overview of a diverse set of exploratory data analysis techniques, such as numeric summary statistics and fundamental data visualization.
Learning Outcomes
By the end of the module students should be able to:
Calculate elementary discrete probabilities by applying standard counting techniques.
Calculate probabilities and conditional probabilities and apply Bayes' Theorem in standard situations.
Understand an apply the theory of discrete and continuous random variables including the properties of expectation and variance and apply them to in standard situations.
Understand exploratory data analysis via computation, simulation, and visualization utilizing statistical software.
Have foundational knowledge of standard univariate distributions and their properties.
Collect, analyse, and correctly interpret data using statistical concepts.
Assessment
Assessment Methods & Exceptions
Assessment:
2hr examination (50%) In-course assessment (50%) (including a variety of assessment possibly including problem sheets, class tests, online quizzes and group projects)
