Description

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences (Int'l Ed)

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£56.28

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Paperback / softback by J. Susan Milton , Jesse Arnold

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This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and... Read more

    Publisher: McGraw-Hill Education - Europe
    Publication Date: 16/11/2002
    ISBN13: 9780071198592, 978-0071198592
    ISBN10: 0071198598

    Number of Pages: 832

    Non Fiction , Computing

    Description

    This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

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