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.
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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
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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