Description

Book Synopsis
Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students'' understanding.

Trade Review
'… succinct and fast-paced …' Bogdan Hoanca, Optics and Photonics News
'… provides innovative and intelligent comments and connecting elements, as well as data analysis and interpretation … [it] extends to fundamental and known issues, which are offered from an understandable point of view.' Nikolaos E. Myridis, Contemporary Physics

Table of Contents
1. Science and statistical data analysis; 2. Statistical summaries of data; 3. Simple statistical inferences; 4. Probability theory; 5. Random variables; 6. Estimation and maximum likelihood; 7. Significance tests and confidence intervals; 8. Monte Carlo methods; Appendixes; References; Index.

Scientific Inference

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    £999.99

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    A Paperback by Simon Vaughan

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      View other formats and editions of Scientific Inference by Simon Vaughan

      Publisher: Cambridge University Press
      Publication Date: 19/09/2013
      ISBN13: 9781107607590, 978-1107607590
      ISBN10:

      Description

      Book Synopsis
      Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students'' understanding.

      Trade Review
      '… succinct and fast-paced …' Bogdan Hoanca, Optics and Photonics News
      '… provides innovative and intelligent comments and connecting elements, as well as data analysis and interpretation … [it] extends to fundamental and known issues, which are offered from an understandable point of view.' Nikolaos E. Myridis, Contemporary Physics

      Table of Contents
      1. Science and statistical data analysis; 2. Statistical summaries of data; 3. Simple statistical inferences; 4. Probability theory; 5. Random variables; 6. Estimation and maximum likelihood; 7. Significance tests and confidence intervals; 8. Monte Carlo methods; Appendixes; References; Index.

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