This is a first course in probability and statistics. The first half broadly introduces the basic notions of probability theory, covering events and random variables, and develops them to the stage where one can begin to use probabilistic ideas in statistical inference and modelling, and the study of stochastic processes. This half also deals with events, the axioms of probability, conditional probability and independence, as well as introducing discrete random variables including distributions, expectation and variance. Joint distributions are also covered. The second half of the module introduces the fundamental ideas of classical statistics. It covers descriptive statistics, the estimation of population moments using data and the basic ideas of statistical inference, hypothesis testing and interval estimation. These methods will be applied to data from a range of applications, including business, economics, science and medicine. A simple statistics package will be used to perform the calculations.

Sorry, there are no lists here yet. You could try:

  • Clicking My Lists from the menu. Your course enrolled lists are stored here.
  • Searching for the list using the form below:

Lists linked to Applied Probability and Statistics

There are currently no lists linked to this Module.