Statistics, Data Analysis, and Decision Modeling, 5th edition

Published by Pearson (July 14, 2021) © 2022

  • James R. Evans University of Cincinnati

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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.

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

For undergraduate and graduate level courses that combines introductory statistics with data analysis or decision modeling.

 

A pragmatic approach to statistics, data analysis and decision modeling.

 

Statistics, Data Analysis & Decision Modeling focuses on the practical understanding of its topics, allowing readers to develop conceptual insight on fundamental techniques and theories. Evans’ dedication to present material in a simple and straightforward fashion is ideal for student comprehension.


Table of contents

Brief Contents

PART I: STATISTICS AND DATA ANALYSIS

  • Chapter 1 Data and Business Decisions
  • Chapter 2 Displaying and Summarizing Data
  • Chapter 3 Probability Distributions and Applications
  • Chapter 4 Sampling and Estimation
  • Chapter 5 Hypothesis Testing and Statistical Inference
  • Chapter 6 Regression Analysis
  • Chapter 7 Forecasting
  • Chapter 8 Statistical Quality Control

PART II: DECISION MODELING AND ANALYSIS

  • Chapter 9 Building and Using Decision Models
  • Chapter 10 Risk Analysis and Monte Carlo Simulation
  • Chapter 11 Decisions, Uncertainty, and Risk
  • Chapter 12 Queues and Process Simulation Modeling
  • Chapter 13 Linear Optimization
  • Chapter 14 Integer and Nonlinear Optimization

Appendix

Author bios

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