Numbers, data, information and evidence are everywhere. How can we pick through the noise to find the signal? What does the evidence tell us? How certain should we be? A comprehensive understanding of the methods used in data analysis is vital to reach appropriate conclusions.
You will gain a comprehensive knowledge of probability, upon which statistical techniques are built. You will learn how to prove mathematical results in probability theory. With a firm foundation in probability, you will develop your skills in statistics, gaining a comprehensive understanding of the reasoning for and methods of statistical inference. You will be able to select appropriate techniques to solve many standard problems, both mathematically and with appropriate software, and critically interpret your results. You will also be ready to study more advanced and non-standard statistical problems.
The module is designed (along with other modules) to satisfy the standards of subject CS1 of the Institute and Faculty of Actuaries examinations for exemption purposes.
64 (Lecture 60, PC 4)
Take home test worth 30%
Examination worth 70%
Reassessment: Like-for-like
Composite form of reassessment for failed components – examination.
On successfully completing the module, students will be able to:
1) Critically appraise and deploy probability theory and statistical inference
2) Apply mathematical techniques to analyse associations between random variables, and study the effects of explanatory variables on response variables through linear regression modelling
3) Apply and evaluate a comprehensive range of mathematical techniques to manipulate probability distributions, calculate point and interval estimates of parameters and to perform tests of hypotheses
4) Critically select and apply the above techniques to solve complex problems
5) Generate and evaluate output from statistical software for probability theory and statistical inference
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