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Published by Chapman and Hall/CRC, 2011
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Published by Chapman and Hall/CRC, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Published by Chapman and Hall/CRC, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
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Published by Chapman and Hall/CRC, 2023
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 1032477725 ISBN 13: 9781032477725
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ISBN 10: 1032477725 ISBN 13: 9781032477725
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Published by Chapman and Hall/CRC, 2011
ISBN 10: 1584889470 ISBN 13: 9781584889472
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ISBN 10: 1032477725 ISBN 13: 9781032477725
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ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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ISBN 10: 1584889470 ISBN 13: 9781584889472
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Published by Chapman and Hall/CRC 2009-06-11, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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ISBN 10: 1584889470 ISBN 13: 9781584889472
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ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Published by Chapman and Hall/CRC, 2011
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Published by Taylor & Francis Inc, Bosa Roca, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Hardcover. Condition: new. Hardcover. Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples--not to perform entire analyses. After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference. Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data. Explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. This title introduces basic concepts of inference through a study of several important procedures, including parametric and nonparametric methods, analysis of variance, and regression. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Chapman and Hall/CRC, 2011
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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ISBN 10: 1584889470 ISBN 13: 9781584889472
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Published by Taylor & Francis Group, 2011
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Published by Chapman and Hall/CRC, 2011
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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ISBN 10: 1584889470 ISBN 13: 9781584889472
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Published by Chapman and Hall/CRC, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Add to basketCondition: New. 2009. 0th Edition. Hardcover. Explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. This title introduces basic concepts of inference through a study of several important procedures, including parametric and nonparametric methods, analysis of variance, and regression. Series: Chapman & Hall/CRC Texts in Statistical Science. Num Pages: 496 pages, 72 black & white illustrations, 30 black & white tables. BIC Classification: PBT. Category: (UU) Undergraduate. Dimension: 238 x 156 x 29. Weight in Grams: 884. . . . . .
Published by Taylor & Francis Inc, Bosa Roca, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Add to basketHardcover. Condition: new. Hardcover. Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples--not to perform entire analyses. After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference. Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data. Explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. This title introduces basic concepts of inference through a study of several important procedures, including parametric and nonparametric methods, analysis of variance, and regression. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketHardcover. Condition: Brand New. 1st edition. 496 pages. 9.61x6.89x1.22 inches. In Stock.
Published by Taylor & Francis Inc, Bosa Roca, 2009
ISBN 10: 1584889470 ISBN 13: 9781584889472
Language: English
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Add to basketHardcover. Condition: new. Hardcover. Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples--not to perform entire analyses. After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference. Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data. Explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. This title introduces basic concepts of inference through a study of several important procedures, including parametric and nonparametric methods, analysis of variance, and regression. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.