Business Statistics, Canadian Edition, 4th edition

Published by Pearson Canada (10 February 2020) © 2021

  • Norean R. Sharpe Georgetown University
  • Richard D. De Veaux Williams College
  • Paul F. Velleman Cornell University (Emetrius)
  • David Wright University of Ottawa

Loose-Leaf

ISBN-13: 9780135469019
Business Statistics, Canadian Edition
Published 2020

Details

  • Print edition
  • Access to MyLab®/Mastering®/Revel® not included

Title overview

The question that motivates a business student’s study of Statistics is “How can I make better decisions?” As entrepreneurs and consultants, we know that in today’s data-rich environment, knowledge of Statistics is essential to survive and thrive in the business world. But, as educators, we’ve seen a disconnect between the way Business Statistics is traditionally taught and the way it should be used in making business decisions. In Business Statistics, we try to narrow the gap between theory and practice by presenting relevant statistical methods that will empower business students to make effective, data-informed decisions.


Statistics is practised with technology. This insight informs everything, from our choice of forms for equations (favouring intuitive forms over calculation forms) to our extensive use of real data. But most important, understanding the value of technology allows us to focus on teaching statistical thinking rather than just calculation. The questions that motivate each of our hundreds of examples are geared not to the question “How do you find the answer?” but rather to the question “Does your data satisfy the necessary assumptions and how do you apply the result to a business situation?” This focus on statistical thinking ties the chapters of the book together.


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Table of contents

  1. An Introduction to Statistics
  2. Data
  3. Surveys and Sampling
  4. Displaying and Describing Categorical Data
  5. Displaying and Describing Quantitative Data
  6. Scatterplots, Association, and Correlation
  7. Introduction to Linear Regression
  8. Randomness and Probability
  9. Random Variables and Probability Distributions
  10. Sampling Distributions
  11. Confidence Intervals for Proportions
  12. Testing Hypotheses About Proportions
  13. Confidence Intervals and Hypothesis Tests for Means
  14. Comparing Two Means
  15. Design of Experiments and Analysis of Variance (ANOVA)
  16. Inference for Counts: Chi-Square Tests
  17. Nonparametric Methods
  18. Inference for Regression
  19. Understanding Regression Residuals
  20. Multiple Regression
  21. Building Multiple Regression Models
  22. Time Series Analysis
  23. Decision Making and Risk
  24. Quality Control
  25. Introduction to Data Mining (Online)

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