I'm a studentI'm an educator

Statistics for Business: Decision Making and Analysis, 3rd edition

Published by Pearson (January 25, 2021) © 2018

  • Robert A. Stine Wharton School of the University of Pennsylvania
  • Dean Foster Wharton School of the University of Pennsylvania
Products list
per month
-month term, pay monthly or pay
Buy nowOpens in a new tab
Instant access

eTextbook features

  • Instant access to eTextbook
  • Search, highlight, and notes
  • Create flashcards
Products list
$170.66

Price Reduced From: $213.32

Details

  • Loose-leaf, 3-hole-punched pages
Products list
$119.99
Buy accessOpens in a new tab
14 day temporary access available

Access details

  • Pearson+ eTextbook with study tools
  • Instant access once purchased
  • Register with a Course ID, a link from your instructor or an LMS link (Blackboardâ„¢, Canvasâ„¢, Moodle or D2L®)

Features

  • Interactive digital learning experience
  • Help when and where you need it
  • Instant feedback on assignments
  • Apps and study tools

Statistics for Business will teach you how to work with data to make sound business decisions. The text uses an application-based approach, with hints in every chapter on using Excel, Minitab Express, and JMP to successfully analyze data. You'll learn how to apply a 4M Analytics decision making strategy -- motivation, method, mechanics and message -- to better understand how the context around a business decision motivates the statistical process and how the results inform a course of action.

The 3rd Edition includes 90 new and updated data sets and more than 100 enhanced exercises. Examples and illustrations have been added to help you make connections between business and data. You'll also get step-by-step instructions in every chapter to walk you through completing analytic exercises with the latest version of Excel.

I. Variation

  1. Introduction
  2. Data
  3. Describing Categorical Data
  4. Describing Numerical Data
  5. Association Between Categorical Variables
  6. Association Between Quantitative Variables

II. Probability

  1. Probability
  2. Conditional Probability
  3. Random Variables
  4. Association Between Random Variables
  5. Probability Models for Counts
  6. The Normal Probability Model

III. Inference

  1. Samples and Surveys
  2. Sampling Variation and Quality
  3. Confidence Intervals
  4. Statistical Tests
  5. Comparison
  6. Inference for Counts

IV. Regression Models

  1. Linear Patterns
  2. Curved Patterns
  3. The Simple Regression Model
  4. Regression Diagnostics
  5. Multiple Regression
  6. Building Regression Models
  7. Categorical Explanatory Variables
  8. Analysis of Variance
  9. Time Series

Supplementary Material (Online-Only)

Alternative Approaches to Inference

Two-Way Analysis of Variance

Regression with Big Data

Need help? Get in touch