Table of Contents

1 The Poisson distribution
The Poisson distribution
The Poisson distribution as an approximation to the binomial distribution
The normal distribution as an approximation to the Poisson distribution
2 Linear combinations of random variables
Linear functions of a random variable
Linear combinations of random variables
The sum of independent Poisson Variables
The sum of independent normal variables
The difference of independent normal Variables
Multiples of normal Variables
3 Continuous probability distributions
Continuous random Variables
Median and quartiles
Mean and Variance
Miscellaneous worked examples
4 Sampling and estimation
Sampling
Sample statistics: the sample mean, X
Unbiased estimates
Confidence intervals for µ, the population mean
Confidence intervals for proportion, p
5 Hypothesis tests 1: Discrete variables
Hypothesis test for a binomial proportion p
Hypothesis test for a Poisson mean
Type I and Type II errors
6 Hypothesis tests 2: z-tests
Introduction to z-tests
Hypothesis test 1: testing µ, the mean of a population
Type I and Type II errors
Hypothesis test 2: testing a binomial proportion p when n is large
Hypothesis test 3: testing a Poisson mean when y is large
Normal distribution tables
List of formulae provided in the exam
Sample exam papers
Answers

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`"Amazing book! It covers all the syllabus topics comprehensively, and it has clearly laid-out and separated sections so that you don't get confused. In my exam, there was not a single question that was unfamiliar because I had already encountered at least one exercise of its type in the worked examples in the book. A truly remarkable book and I recommend it vividly."'
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