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

    Complete Probability & Statistics 2 for Cambridge International AS & A Level by Nicholson, James;

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    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

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    Product details:

    • Edition number 2
    • Publisher OUP Oxford
    • Date of Publication 12 July 2018

    • ISBN 9780198425175
    • Binding Unidentified
    • No. of pages208 pages
    • Size 247x190x10 mm
    • Weight 466 g
    • Language English
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    Categories

    Short 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.

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    Long description:

    Support achievement in the latest syllabus (9709), for examination from 2020, with a stretching, practice-driven approach that builds the advanced skills required for Cambridge exam success and progression to further study.

    This new edition is fully aligned with the Probability & Statistics 2 part of the latest International AS & A Level syllabus, and contains a comprehensive mapping grid so you can be sure of complete support.

    Get students ready for higher education with a focus on real world application. From parabolic reflectors to technology in sport, up-to-date, international examples show how mathematics is used in real life.

    Students have plenty of opportunities to hone their skills with extensive graduated practice and thorough worked examples. Plus, give students realistic practice for their exams with exam-style questions covering every topic.

    Answers are included in the back of the book with full step-by-step solutions for all exercises and exam-style questions available on the accompanying support site.

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    Table of Contents:

    Syllabus matching grid
    1 The Poisson distribution
    Introducing the Poisson distribution
    The role of the parameter of the Poisson distribution
    The recurrence relation for the Poisson distribution
    Mean and variance of the Poisson distribution
    Modelling with the Poisson distribution
    2 Approximations involving the Poisson distribution
    Poisson as an approximation to the Binomial
    The Normal approximation to the Poisson distribution
    3 Linear combination of random variables
    Expectation and variance of a linear function of a random variable
    Linear combination of two (or more) independent random variables
    Expectation and variance of a sum of repeated independent observations of a random variable, and the mean of those observations
    Comparing the sum of repeated independent observations with the multiple of a single observation
    Review exercise A
    Maths in real-life: The mathematics of the past
    4 Linear combination of Poisson and Normal variables
    The distribution of the sum of two independent Poisson random variables
    Linear functions and combinations of normal random variables
    5 Continuous random variables
    Introduction to continuous random variables
    Probability density functions
    Mean and variance of a continuous random variable
    Mode of a continuous random variable
    6 Sampling
    Populations, census and sampling
    Advantages and disadvantages of sampling
    Variability between samples and use of random numbers
    The sampling distribution of a statistic
    Sampling distribution of the mean of repeated observations of a random variable
    Sampling distribution of the mean of a sample from a normal distribution
    The Central Limit Theorem
    Descriptions of some sampling methods
    Review exercise B
    Maths in real-life: Modelling statistics
    7 Estimation
    Interval estimation
    Unbiased estimate of the population mean
    Unbiased estimate of the population variance
    Confidence intervals for the mean of a Normal distribution
    Confidence intervals for the mean of a large sample from any distribution
    Confidence intervals for a proportion
    8 Hypothesis testing for discrete distributions
    The logical basis for hypothesis testing
    Critical region
    Type I and Type II errors
    Hypothesis test for the proportion p of a Binomial distribution
    Hypothesis test for the mean of a Poisson distribution
    9 Hypothesis testing using the Normal distribution
    Hypothesis test for the mean of a Normal distribution
    Hypothesis test for the mean using a large sample
    Using a confidence interval to carry out a hypothesis test
    Review exercise C
    Maths in real-life: A risky business
    List of formulae
    Answers
    Glossary of terms
    Index

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