9780135131992

Statistics : The Art and Science of Learning from Data

  • ISBN 13:

    9780135131992

  • ISBN 10:

    0135131995

  • Edition: 2nd
  • Format: Hardcover
  • Copyright: 01/17/2013
  • Publisher: Pearson
  • Newer Edition

Note: Not guaranteed to come with supplemental materials (access cards, study guides, lab manuals, CDs, etc.)

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Summary

KEY MESSAGE: Alan Agresti and Chris Franklin have merged their research and classroom experience to develop this successful introductory statistics text.Statistics: The Art and Science of Learning from Data, Second Editionhelps readers become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to readers without compromising necessary rigor. The varied and data-rich examples and exercises place heavy emphasis on thinking about and understanding statistical concepts. The applications are topical and current, and successfully illustrate the relevance of statistics. The authors believe that it is important for readers to be comfortable with analyzing both quantitative and categorical data. Every day in the media, percentages and rates are used to summarize opinion polls, outcomes of medical studies, and economic reports. As a result, greater attention is paid to the analysis of proportions than is typical of many introductory statistics texts. The text maintains its commitment to the recommendations of the ASA endorsed GAISE (Guidelines for Assessment for Instruction in Statistical Education) Report. KEY TOPICS: Statistics: The Art and Science of Learning from Data; Exploring Data with Graphs and Numerical Summaries; Association: Contingency, Correlation, and Regression; Gathering Data; Probability in our Daily Lives; Probability Distributions; Sampling Distributions; Statistical Inference: Confidence Intervals; Statistical Inference: Significance Tests about Hypothesis; Comparing Two Groups; Analyzing the Associations Between Categorical Variables; Analyzing Association Between Quantitative Variables: Regression Analysis; Multiple Regression; Comparing Groups: Analysis of Variance Methods; Nonparametric Statistics MARKET: For all readers interested in statistics.

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