Business Statistics Made Easy in SAS
by Gregory Lee
SAS Institute | October  2015 | ISBN-10: 1629598410 | ePUB | 30.1 mb

Learn or refresh core statistical methods for business with SAS® and approach real business analytics issues and techniques using a practical approach that avoids complex mathematics and instead employs easy-to-follow explanations. 
Business Statistics Made Easy in SAS® is designed as a user-friendly, practice-oriented, introductory text to teach businesspeople, students, and others core statistical concepts and applications. It begins with absolute core principles and takes you through an overview of statistics, data and data collection, an introduction to SAS®, and basic statistics (descriptive statistics and basic associational statistics). The book also provides an overview of statistical modeling, effect size, statistical significance and power testing, basics of linear regression, introduction to comparison of means, basics of chi-square tests for categories, extrapolating statistics to business outcomes, and some topical issues in statistics, such as big data, simulation, machine learning, and data warehousing. The book steers away from complex mathematical-based explanations, and it also avoids basing explanations on the traditional build-up of distributions, probability theory and the like, which tend to lose the practice-oriented reader. Instead, it teaches the core ideas of statistics through methods such as careful, intuitive written explanations, easy-to-follow diagrams, step-by-step technique implementation, and interesting metaphors. With no previous SAS experience necessary, Business Statistics Made Easy in SAS® is an ideal introduction for beginners. It is suitable for introductory undergraduate classes, postgraduate courses such as MBA refresher classes, and for the business practitioner. It is compatible with SAS® University Edition."

About the Author
Professor Gregory John Lee is currently the Research Director and an Associate Professor in Research Methodology and Decision Sciences at the AMBA-rated Wits Business School, Johannesburg, South Africa. He has authored books on HR Metrics, and has published many articles in the Human Resource Management Journal, European Journal of Operational Management, Scientometrics, Journal of Business-to-Business Marketing, International Journal of HRM, International Journal of Manpower, Review of Income & Wealth, and Journal of Human Resource Costing & Accounting to name but a few. Lee focuses on issues in human resource management, notably HR metrics, in which he has established himself as a leading expert, and other areas such as training, employee turnover, and the employee-customer link. He has served in many capacities within the international academic field and has sat on the GMAC Advisory Council, the editorial board of the Journal of Organizational and Occupational Psychology, and he engages in frequent reviewing for many journals. In addition, Lee is a well-known consultant, writer, and speaker in the corporate and practical management arenas, notably in the area of HR metrics but extending to other areas such as human resources strategy and foresight.

CONTENTS
Chapter 1: Introduction to the Central Text book Example
Chapter 2: Introduction to the Statistics Process
Chapter 3: Introduction to Data
Chapter 4: Data Collection & Capture
Chapter 5: Introduction to SAS*
Chapter 6: Basics of SAS Programs, Data Manipulation, Analysis & Reporting
Chapter 7: Descriptive Statistics: Understand your Data
Chapter 8: Basics of Associating Variables
Chapter 9: Using Basic Statistics to Check & Fix Data
Chapter 10: Introduction to Graphing in SAS
Chapter 11: TheStatistics Process: Fitting Modelsto Data
Chapter 12: Key Concepts: Size & Accuracy
Chapter 13: Introduction to Linear Regression
Chapter 14: Categories Explaining a Continuous Variable: Comparing Two Means
Chapter 15: Categorical Data Distributions & Associations
Chapter 16: Reporting Business Analytics
Chapter 17: Business Analysis from Statistics: Introduction
Chapter 18: Miscallaneous Business Statistics Topics
Chapter 19: Bibliography
 
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