Business Statistics, Canadian Edition, 4th edition

Published by Pearson Canada (February 10, 2020) © 2021

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

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Products list

In this eTextbook — More ways to learn

  • More flexible. Start learning right away, on any device.
  • More supportive. Get AI explanations and practice questions (select titles).
  • More interactive. Bring learning to life with audio, videos, and diagrams.
  • More memorable. Make concepts stick with highlights, search, notes, and flashcards.
  • More understandable. Translate text into 100+ languages with one tap.

Title overview

Business Statistics narrows the gap between theory and practice, by covering relevant and real-life statistical methods that help business students make good, data-driven decisions. With their unique blend of teaching, consulting, and entrepreneurial experiences, this dynamic author team brings a modern edge to teaching statistics to business students. Focusing on stats in the context of real business issues, with an emphasis on analysis and understanding over computation, the text helps students to be analytical, prepares them to make better business decisions, and shows them how to effectively communicate results.

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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