 \$26.99

# Complete Probability & Statistics 2 for Cambridge International AS & A Level

By James Nicholson
US\$ 26.99
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Book Description

Providing complete syllabus support (9709), this stretching and practice-focused course builds the advanced skills needed for the latest Cambridge assessments and the transition to higher education. Engaging, real world examples make mathematics relevant to real life.

• Front Cover
• IFC
• Title Page
• Imprint
• Contents
• Introduction
• 1 The Poisson distribution
• 1.1 Introducing the Poisson distribution
• 1.2 The role of the parameter of the Poisson distribution
• 1.3 The recurrence relation for the Poisson distribution
• 1.4 Mean and variance of the Poisson distribution
• 1.5 Modelling with the Poisson distribution
• 2 Approximations involving the Poisson distribution
• 2.1 Poisson as an approximation to the binomial
• 2.2 The normal approximation to the Poisson distribution
• 3 Linear combination of random variables
• 3.1 Expectation and variance of a linear function of a random variable
• 3.2 Linear combination of two (or more) independent random variables
• 3.3 Expectation and variance of a sum of repeated independent observations of a random variable, and the mean of those observations
• 3.4 Comparing the sum of repeated independent observations with the multiple of a single observation
• Maths in real-life: The mathematics of the past
• 4 Linear combination of Poisson and normal variables
• 4.1 The distribution of the sum of two independent Poisson random variables
• 4.2 Linear functions and combinations of normal random variables
• 5 Continuous random variables
• 5.1 Introduction to continuous random variables
• 5.2 Probability density functions
• 5.3 Mean and variance of a continuous random variable
• 5.4 Mode of a continuous random variable
• 6 Sampling
• 6.1 Populations, census and sampling
• 6.3 Variability between samples and use of random numbers
• 6.4 The sampling distribution of a statistic
• 6.5 Sampling distribution of the mean of repeated observations of a random variable
• 6.6 Sampling distribution of the mean of a sample from a normal distribution
• 6.7 The Central Limit Theorem
• 6.8 Descriptions of some sampling methods
• Maths in real-life: Modelling statistics
• 7 Estimation
• 7.1 Interval estimation
• 7.2 Unbiased estimate of the population mean
• 7.3 Unbiased estimate of the population variance
• 7.4 Confidence intervals for the mean of a normal distribution
• 7.5 Confidence intervals for the mean of a large sample from any distribution
• 7.6 Confidence intervals for a proportion
• 8 Hypothesis testing for discrete distributions
• 8.1 The logical basis for hypothesis testing
• 8.2 Critical region
• 8.3 Type I and Type II errors
• 8.4 Hypothesis test for the proportion p of a binomial distribution
• 8.5 Hypothesis test for the mean of a Poisson distribution
• 9 Hypothesis testing using the normal distribution
• 9.1 Hypothesis test for the mean of a normal distribution
• 9.2 Hypothesis test for the mean using a large sample
• 9.3 Using a confidence interval to carry out a hypothesis test
• Maths in real-life: A risky business
• Exam-style paper A
• Exam-style paper B
• Tables of the normal distribution
• Glossary
• Index
• Back Cover
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