American English

Statistics for Managers Using Microsoft Excel, Global Edition ,9th edition::9781292338309

Published by Pearson (June 8, 2020) © 2020

David Levine | David Stephan | Kathryn Szabat
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    ISBN-13: 9781292338309

    Statistics for Managers Using Microsoft Excel, Global Edition ,9th edition

    Language: American English

    For one-semester courses in Introduction to Business Statistics.

     

    The gold standard in learning Microsoft Excel for business statistics

    Statistics for Managers Using Microsoft® Excel®9th Edition, Global Edition helps students develop the knowledge of Excel needed in future careers. The authors present statistics in the context of specific business fields, and now include a full chapter on business analytics. Guided by principles set forth by ASA’s Guidelines for Assessment and Instruction (GAISE) reports and the authors’ diverse teaching experiences, the text continues to innovate and improve the way this course is taught to students. Current data throughout gives students valuable practice analyzing the types of data they will see in their professions, and the authors’ friendly writing style includes tips and learning aids throughout. 

     

    The book also integrates PHStat, a statistical add-in that bolsters the functions of Excel. Extensive instructor and student resources are provided, including two online-only chapters, as well as the Digital Cases referenced in the text. 

     

    • 1 Defining and Collecting Data
    • 2 Organizing and Visualizing Variables
    • 3 Numerical Descriptive Measures
    • 4 Basic Probability
    • 5 Discrete Probability Distributions
    • 6 The Normal Distribution and Other Continuous Distributions
    • 7 Sampling Distributions
    • 8 Confidence Interval Estimation
    • 9 Fundamentals of Hypothesis Testing: One-Sample Tests
    • 10 Two-Sample Tests
    • 11 Analysis of Variance
    • 12 Chi-Square and Nonparametric Tests
    • 13 Simple Linear Regression
    • 14 Introduction to Multiple Regression
    • 15 Multiple Regression Model Building
    • 16 Time-Series Forecasting
    • 17 Business Analytics
    • 18 Getting Ready to Analyze Data in the Future

    Download the detailed table of contents