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• Syllabus matching grid 1 Introduction to statistical thinking 1.1: What is statistics and why is it important? 1.2: Types of data 2 Measures of location and spread 2.1: Averages 2.2: Quartiles and the interquartile range 2.3: Variance and standard deviation 2.4: Which average should you use? 2.5: Coding 3 Representing and analysing data 3.1: Stem-and-leaf diagrams 3.2: Box-and-whisker plots 3.3: Histograms 3.4: Cumulative frequency graphs 3.5: Skewness 3.6: Comparing distributions Review exercise A Maths in real-life: Seeing the wood and the trees 4 Probability 4.1: Basic concepts and language f probability 4.2: Two (or more) events 4.3: Tree diagrams 4.4: Conditional probability 4.5: Relationships between events 5 Probability distributions and discrete random variables 5.1: Discrete random variables 5.2: The probability function, p(x) 5.3: Expectation of a discrete random variable 5.4: The variance of a discrete random variable 6 Permutations and combinations 6.1: Permutations of n distinct objects in a straight line 6.2: Permutations of k objects from distinct objects in a straight line 6.3: Allowing constraints on permutations (for n distinct objects) 6.4: Permutations when some objects are not distinguishable 6.5: Combinations 6.6: Evaluate probabilities by calculation sing permutations or combinations Review exercise B Maths in real-life: Sporting statistics 7 The binomial distribution 7.1: Introducing the binomial distribution 7.2: Mean and variance of the binomial distribution 7.3: Modelling with the binomial distribution 8 The geometric distribution 8.1: Introducing the geometric distribution 8.2: The mean of the geometric distribution 9 The normal distribution 9.1: Continuous probability distributions and the normal distribution 9.2: Standard normal distribution 9.3: Calculating probabilities for the (µ, *s2) distribution 9.4: Using the normal distribution 10 The normal approximation to the binomial distribution 10.1: Normal shape of some binomial distributions 10.2: Continuity correction 10.3: The parameters for the normal approximation Review exercise C Maths in real-life: Statistics is definitely not a lonely world Exam-style paper A Exam-style paper B Answers Data sets Glossary of terms Index

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• Syllabus matching grid 1 Introduction to statistical thinking 1.1: What is statistics and why is it important? 1.2: Types of data 2 Measures of location and spread 2.1: Averages 2.2: Quartiles and the interquartile range 2.3: Variance and standard deviation 2.4: Which average should you use? 2.5: Coding 3 Representing and analysing data 3.1: Stem-and-leaf diagrams 3.2: Box-and-whisker plots 3.3: Histograms 3.4: Cumulative frequency graphs 3.5: Skewness 3.6: Comparing distributions Review exercise A Maths in real-life: Seeing the wood and the trees 4 Probability 4.1: Basic concepts and language f probability 4.2: Two (or more) events 4.3: Tree diagrams 4.4: Conditional probability 4.5: Relationships between events 5 Probability distributions and discrete random variables 5.1: Discrete random variables 5.2: The probability function, p(x) 5.3: Expectation of a discrete random variable 5.4: The variance of a discrete random variable 6 Permutations and combinations 6.1: Permutations of n distinct objects in a straight line 6.2: Permutations of k objects from distinct objects in a straight line 6.3: Allowing constraints on permutations (for n distinct objects) 6.4: Permutations when some objects are not distinguishable 6.5: Combinations 6.6: Evaluate probabilities by calculation sing permutations or combinations Review exercise B Maths in real-life: Sporting statistics 7 The binomial distribution 7.1: Introducing the binomial distribution 7.2: Mean and variance of the binomial distribution 7.3: Modelling with the binomial distribution 8 The geometric distribution 8.1: Introducing the geometric distribution 8.2: The mean of the geometric distribution 9 The normal distribution 9.1: Continuous probability distributions and the normal distribution 9.2: Standard normal distribution 9.3: Calculating probabilities for the (µ, *s2) distribution 9.4: Using the normal distribution 10 The normal approximation to the binomial distribution 10.1: Normal shape of some binomial distributions 10.2: Continuity correction 10.3: The parameters for the normal approximation Review exercise C Maths in real-life: Statistics is definitely not a lonely world Exam-style paper A Exam-style paper B Answers Data sets Glossary of terms Index

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• Syllabus matching grid 1 Introduction to statistical thinking 1.1: What is statistics and why is it important? 1.2: Types of data 2 Measures of location and spread 2.1: Averages 2.2: Quartiles and the interquartile range 2.3: Variance and standard deviation 2.4: Which average should you use? 2.5: Coding 3 Representing and analysing data 3.1: Stem-and-leaf diagrams 3.2: Box-and-whisker plots 3.3: Histograms 3.4: Cumulative frequency graphs 3.5: Skewness 3.6: Comparing distributions Review exercise A Maths in real-life: Seeing the wood and the trees 4 Probability 4.1: Basic concepts and language f probability 4.2: Two (or more) events 4.3: Tree diagrams 4.4: Conditional probability 4.5: Relationships between events 5 Probability distributions and discrete random variables 5.1: Discrete random variables 5.2: The probability function, p(x) 5.3: Expectation of a discrete random variable 5.4: The variance of a discrete random variable 6 Permutations and combinations 6.1: Permutations of n distinct objects in a straight line 6.2: Permutations of k objects from distinct objects in a straight line 6.3: Allowing constraints on permutations (for n distinct objects) 6.4: Permutations when some objects are not distinguishable 6.5: Combinations 6.6: Evaluate probabilities by calculation sing permutations or combinations Review exercise B Maths in real-life: Sporting statistics 7 The binomial distribution 7.1: Introducing the binomial distribution 7.2: Mean and variance of the binomial distribution 7.3: Modelling with the binomial distribution 8 The geometric distribution 8.1: Introducing the geometric distribution 8.2: The mean of the geometric distribution 9 The normal distribution 9.1: Continuous probability distributions and the normal distribution 9.2: Standard normal distribution 9.3: Calculating probabilities for the (µ, *s2) distribution 9.4: Using the normal distribution 10 The normal approximation to the binomial distribution 10.1: Normal shape of some binomial distributions 10.2: Continuity correction 10.3: The parameters for the normal approximation Review exercise C Maths in real-life: Statistics is definitely not a lonely world Exam-style paper A Exam-style paper B Answers Data sets Glossary of terms Index