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The art of statistics : how to learn from data / David Spiegelhalter.

By: Spiegelhalter, D. J [author.].
Publisher: New Delhi : Pelican (Penguin), 2019.Edition: First Indian edition.Description: xvi, 426 p. : illustrations ; 25 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780241258767 (pbk.); 9780241398630 (hbk.); 9781541618510; 1541618513.Subject(s): Statistics -- Popular worksDDC classification: 519.5
Contents:
Getting things done in proportion : categorical data and percentages -- Summarizing and communicating numbers, lots of numbers -- Why are we looking at data anyway? : populations and measurement -- What causes what? -- Modelling relationships using regression -- Algorithms, analytics and prediction -- How sure can we be about what is going on? : estimates and intervals -- Probability : the language of uncertainty and variability -- Putting probability and statistics together -- Answering questions and claiming discoveries -- Learning from experience the Bayesian way -- How things go wrong -- How we can do statistics better --
Summary: Shows how to apply statistical reasoning to real-world problems. This isn't simply memorizing formulas or using the tools in a spreadsheet: he emphasizes the importance of clarifying questions, assumptions, and expectations, and--more importantly--knowing how to responsibly interpret the results the software generates.-- Source other than the Library of Congress.
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Item type Current location Call number Copy number Status Date due
Monograph Monograph Indian Institute of Management Udaipur
B5/3
519.5 (Browse shelf) 1 Available

Includes bibliographical references (pages 407-418) and index.

Introduction -- Getting things done in proportion : categorical data and percentages -- Summarizing and communicating numbers, lots of numbers -- Why are we looking at data anyway? : populations and measurement -- What causes what? -- Modelling relationships using regression -- Algorithms, analytics and prediction -- How sure can we be about what is going on? : estimates and intervals -- Probability : the language of uncertainty and variability -- Putting probability and statistics together -- Answering questions and claiming discoveries -- Learning from experience the Bayesian way -- How things go wrong -- How we can do statistics better -- In conclusion.

Shows how to apply statistical reasoning to real-world problems. This isn't simply memorizing formulas or using the tools in a spreadsheet: he emphasizes the importance of clarifying questions, assumptions, and expectations, and--more importantly--knowing how to responsibly interpret the results the software generates.-- Source other than the Library of Congress.

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