Ramdan Hours:
Sun - Thu
9.30 AM - 2.30 PM
Iftar in --:--:--
🌙 Maghrib: --:--
Image from Google Jackets

Statistics and scientific method : an introduction for students and researchers / Peter J. Diggle and Amanda G. Chetwynd.

By: Contributor(s): Material type: TextTextPublication details: New York : Oxford University Press, 2011.Description: xiii, 172 p., [2] p. of plates : : ill., (some col.) ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780199543199 (pbk.)
Subject(s): DDC classification:
  • 519.5 22 D.P.S
LOC classification:
  • Q180.55.S7 D54 2011
Contents:
Machine generated contents note: -- 1. Introduction -- 2. Overview -- 3. Uncertainty -- 4. Exploratory data analysis -- 5. Experimental design -- 6. Simple comparative experiments -- 7. Statistical modelling -- 8. Survival analysis -- 9. Time series analysis -- 10. Spatial statistics.
Summary: "Most introductory statistics text-books are written either in a highly mathematical style for an intended readership of mathematics undergraduate students, or in a recipe-book style for an intended audience of non-mathematically inclined undergraduate or postgraduate students, typically in a single discipline; hence, "statistics for biologists", "statistics for psychologists", and so on. An antidote to technique-oriented service courses, Statistics and Scientific Method is different. It studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, the text aims to give the reader a clear understanding of how core statistical ideas of experimental design, modelling and data analysis are integral to the scientific method. Aimed primarily at beginning postgraduate students across a range of scientific disciplines (albeit with a bias towards the biological, environmental and health sciences), it therefore assumes some maturity of understanding of scientific method, but does not require any prior knowledge of statistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation. Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice, R, whilst the book's web-page includes downloadable data and R code that enables the reader to reproduce all of the analyses in the book and, with easy modifications, to adapt the code to analyse their own data if they wish. However, the book is not intended to be a textbook on statistical computing, and all of the material in the book can be understood without using either R or any other computer software"--
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Status Date due Barcode
Books Books Main library A8 Non-fiction 519.5 D.P.S (Browse shelf(Opens below)) Available 00009260

Includes bibliographical references and index.

Machine generated contents note: -- 1. Introduction -- 2. Overview -- 3. Uncertainty -- 4. Exploratory data analysis -- 5. Experimental design -- 6. Simple comparative experiments -- 7. Statistical modelling -- 8. Survival analysis -- 9. Time series analysis -- 10. Spatial statistics.

"Most introductory statistics text-books are written either in a highly mathematical style for an intended readership of mathematics undergraduate students, or in a recipe-book style for an intended audience of non-mathematically inclined undergraduate or postgraduate students, typically in a single discipline; hence, "statistics for biologists", "statistics for psychologists", and so on. An antidote to technique-oriented service courses, Statistics and Scientific Method is different. It studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, the text aims to give the reader a clear understanding of how core statistical ideas of experimental design, modelling and data analysis are integral to the scientific method. Aimed primarily at beginning postgraduate students across a range of scientific disciplines (albeit with a bias towards the biological, environmental and health sciences), it therefore assumes some maturity of understanding of scientific method, but does not require any prior knowledge of statistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation. Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice, R, whilst the book's web-page includes downloadable data and R code that enables the reader to reproduce all of the analyses in the book and, with easy modifications, to adapt the code to analyse their own data if they wish. However, the book is not intended to be a textbook on statistical computing, and all of the material in the book can be understood without using either R or any other computer software"--

There are no comments on this title.

to post a comment.