To reinforce basic ideas related to the description and analysis of data, and provide the basis for the application of statistical modelling, estimation, hypothesis testing and regression.
This module follows on from Probability and Statistics A. It develops the basic ideas used in statistical analysis and inference, with an emphasis on how we learn from data using both graphical techniques and statistical methodology based on probability theory. Topics presented include: analysis of simple data; construction of statistical models; sampling distributions and properties of estimators; method of moments and introduction to maximum likelihood estimation; inference for data from one population; comparisons of data from two populations; confidence intervals with samples from one or two populations; hypothesis testing; issues related to association between two variables; linear regression; simulation and statistical computing.
After studying this module, students should be able to:
J.E. Freundís mathematical statistics, by I. Miller and M. Miller, 6th ed., Prentice-Hall, 1999.
Two-hour written examination (at least 80%); continuous assessment (not more than 20%)
Actuarial Mathematics and Statistics,
School of Mathematical and Computer Sciences ,
Heriot-Watt University, Edinburgh EH14 4AS, Scotland
Phone: +44 (0)131 451 3202, Fax +44 (0)131 451 3327 or Email firstname.lastname@example.org