Modern Statistics: A Canadian Perspective by William M GoodmanModern Statistics: A Canadian Perspective by William M Goodman

Modern Statistics: A Canadian Perspective

byWilliam M Goodman

Hardcover | February 8, 2008

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Computers have revolutionized what can be done in statistics and how it can be done, but introductory statistics textbooks have not always kept pace. Maximizing the potential of a computer-enriched, introductory statistics course by acknowledging what the computer can do, Goodman has discarded outdated tables and procedures, introduced when it was assumed calculation could only be done by pen and calculator. Enhancing the content and presentation of traditional methods, Goodman offers a fresh, experiential introduction to statistical concepts and calculations, while providing new possibilities for statistical exploration and experience. The goal of Modern Statistics is to take full advantage of the computer resources now available to students of statistics, fully integrating the coverage of the statistics curriculum with the related coverage of relevant statistical software. Goodman has thus created a modern approach to statistical methods -- an approach that encourages and promotes critical thinking in the application and interpretation of modern statistical techniques.
Title:Modern Statistics: A Canadian PerspectiveFormat:HardcoverDimensions:752 pages, 10.9 × 8.6 × 1.5 inPublished:February 8, 2008Publisher:Nelson College IndigenousLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0176251790

ISBN - 13:9780176251796


Table of Contents

Part 1: Statistical Data Chapter 1: Introduction to Statistical Data Chapter 2: Obtaining the DataPart 2: Descriptions of Data Chapter 3: Displaying Data Distributions Chapter 4: Measures of Location Chapter 5: Measures of Spread and Shape Part 3: Probability and Distributions Chapter 6: Concepts of Probability Chapter 7: Discrete Probability Distributions Chapter 8: Continuous Probability Distributions Part 4: Samples and Estimates Chapter 9: Introduction to Sampling Distributions Chapter 10: Estimates and Confidence Intervals Part 5: Tests for Statistical Significance Chapter 11: One-Sample Tests of Significance Chapter 12: Two-Sample Tests of Significance Chapter 13: Non-Parametric Tests of Significance Chapter 14: Analysis of Variance (Anova)Part 6: Measures and Tests for Association Chapter 15: Measures and Tests for Association Chapter 16: Multiple Linear Regression Chapter 17: Association with Time: Time Series Analysis