Statistics, Data Analysis, and Decision Modeling

Series
Pearson
Author
James R. Evans  
Publisher
Pearson
Cover
Softcover
Edition
5
Language
English
Total pages
560
Pub.-date
April 2012
ISBN13
9780273768227
ISBN
0273768220
Related Titles


Product detail

Product Price CHF Available  
9780273768227
Statistics, Data Analysis, and Decision Modeling
88.90 approx. 7-9 days

eBook

You'll find the eBook here.:

Free evaluation copy for lecturers


Description

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.




Features

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.

Excel 2007 focus with accompanying Excel Add-Ins: This feature allows students to focus more on the interpretation of results as well as the managerial implications of those results.

 

Excel and Add-In explanation place in “Notes”: By separating this feature from the text, the explanation does not get in the way of the narrative and conceptual understanding yet still enhances comprehension.

 

Material re-organization:

  • Theory and extensive computational formulas moved to end of chapter appendices: Separating the formulas from the chapter material provides professors with instructing flexibility and encourages students to focus on the concepts first and the application second.
  • The end of chapter material now includes three different types of problems: The incorporation of three different types of problems gives professors flexibility on what concepts they want students to practice on.
  • Completely re-written Instructor’s Manual created by the book author.

New to this Edition

The fifth edition of this text has been carefully revised to improve clarity and pedagogical features, and incorporate new and revised topics. Many significant changes have been made, and include the following:

  1. Spreadsheet-based tools and applications are compatible with Microsoft Excel 2010, which is used throughout this edition.
  2. Every chapter has been carefully revised to improve clarity. Many explanations of critical concepts have been enhanced using new business examples and data sets.  The sequencing of several topics have been reorganized to improve their flow within the book.  
  3. Excel, PHStat, and other software notes have been moved to chapter appendixes so as not to disrupt the flow of the text.
  4. “SkillBuilder” exercises, designed to provide experience with applying Excel, have been located in the text to facilitate immediate application of new concepts.
  5. Data used in many problems have been changed, and new problems have been added.

Table of 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


Instructor Resources