MEI A Level Further Mathematics Statistics 4th Edition
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Description
Contents
Reviews
Language
English
ISBN
9781510429895
Cover
Title Page
Copyright
Contents
Getting the most from this book
Prior knowledge
1 Statistical problem solving
1.1 The problem solving cycle
2 Discrete random variables
2.1 Notation and conditions for a discrete random variable
2.2 Expectation and variance
3 Discrete probability distributions
3.1 The binomial distribution
3.2 The Poisson distribution
3.3 Link between binomial and Poisson distributions
3.4 Other discrete distributions
4 Bivariate data (correlation coefficients)
4.1 Describing variables
4.2 Interpreting scatter diagrams
4.3 Product moment correlation
4.4 Rank correlation
5 Bivariate data (regression lines)
5.1 The least squares regression line (random on non-random)
5.2 The least squares regression line (random on random)
6 Chi-squared tests
6.1 The chi-squared test for a contingency table
6.2 Goodness of fit tests
Practice questions: Set 1
7 Conditional probability
7.1 Screening tests
7.2 Bayes’ theorem
8 Continuous random variables
8.1 Probability density function
8.2 Expectation and variance
8.3 The median
8.4 The mode
8.5 The continuous uniform (rectangular) distribution
8.6 The exponential distribution
8.7 The expectation and variance of a function of X
8.8 The cumulative distribution function
9 Expectation algebra and the Normal distribution
9.1 The sums and differences of Normal variables
9.2 Modelling discrete situations
9.3 More than two independent random variables
9.4 The distribution of the sample mean
9.5 The central limit theorem
10 Confidence intervals
10.1 The theory of confidence intervals
10.2 Interpreting sample data using the t distribution
11 Hypothesis testing
11.1 Hypothesis testing on a sample mean using the Normal distribution
11.2 Large samples
11.3 Hypothesis testing on a sample mean using the t distribution
11.4 The Wilcoxon signed rank test on a sample median
12 Simulation
12.1 Simulating discrete uniform distributions
12.2 Simulating continuous uniform distributions
12.3 Simulating Normal distributions
12.4 Simulating other distributions
12.5 Simulation and the central limit theorem
Practice questions: Set 2
Answers
Index
Back Cover
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