This module provides a first course in probability and statistics.
The first half introduces the basic notions of probability theory 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. The first section deals with events, the axioms of probability, conditional probability and independence. The second introduces discrete random variables including distributions, expectation and variance. Joint distributions are covered briefly.
The second half 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.
The first half introduces the basic notions of probability theory 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. The first section deals with events, the axioms of probability, conditional probability and independence. The second introduces discrete random variables including distributions, expectation and variance. Joint distributions are covered briefly.
The second half 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.
