Business Analytics, Second Edition teaches the fundamental concepts of the emerging field of business analytics and provides vital tools in understanding how data analysis works in today’s organizations. Students will learn to apply basic business analytics principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. Included access to commercial grade analytics software gives students real-world experience and career-focused value. Author James Evans takes a balanced, holistic approach and looks at business analytics from descriptive, and predictive perspectives.
 
New to This Edition
New and Updated for this Edition
Screenshots throughout the text are updated for Excel® 2013.
The updated design strikes a better balance between the text and the image size.
More problems have been added at the end of every chapter.
There is a new case on Drout Advertising Research.
Content Updates
New and Updated for this Edition
Screenshots throughout the text are updated for Excel® 2013.
The updated design strikes a better balance between the text and the image size.
More problems have been added at the end of every chapter.
There is a new case on Drout Advertising Research.
Content Updates
Chapter 1 has been heavily revised with updated sections and new examples throughout
Chapter 2
New objective–Use Excel functions for business intelligence queries in database
New information on VLOOKUP function
Chapter 3
New section on Data Visualization with Figures and Captures
New examples:
Data Visualization through formal conditioning
Examples of Sparklines
Using Slicers
New Analytics in Practice Box: Driving Business Transformation with IBM Business Analytics
Chapter 4 includes a revised section on the CORREL function
Chapter 5
New section on Join and Marginal Probability
New example–Applying Probability Rules to Joint Events
Chapter 7
New section: Confidence Intervals and Hypothesis Tests
New section: Cautions in Using the Chi-Square Test
Chapter 8
New learning objective: List the Common Types of Mathematical Functions Used in Predictive Modeling
New section: Practical Issues in Trendline and Regression Modeling
Chapter 10
New section: Data Exploration
New example: Using XLMiner to Sample from a Worksheet
New example: A Boxplot for Credit Risk Data
Chapter 11
New learning objective: Use Excel tools to create user-friendly Excel Models and Applications
New section: Spreadsheet Applications in Business Analytics
New section: Developing User-Friendly Excel Applications
New example: Using Data Validation
New example: Using Form Controls for the Outsourcing Decision Model
Chapter 13 includes a new example: Multiple Parameter Analysis for the SSC Problem
Chapter 14
New section: Solver Output and Data Visualization
New example: Little Investment Advisers
New section on scaling
Chapter 16
New section: Risk and Variability