Statistical Modeling And Data Validation made Easy for Research Scholars And Analytics Professionals

Shailendra Kadre

10th March, 2015

Statistical methods are used very extensively in many business domains, sociology, economics and in the scientific domains like life sciences, and so on. More than 70% research projects use quantitative methods. Quantitative research involving statistical methodologies may start with collection of a large amount of data - may be based upon a hypothesis, a theory or it may even result from financial transactions involving credit cards and other data sources. This kind of data is called raw data and it usually needs recording, verification and validation before it can be used for any further analysis. Data analytics needs a scientific approach towards problem solving.  The typical steps involved are

1. Identification of data sources
2. Data collection and recording it in a homogeneous form like relational database tables. The data recording methodologies may differ very from one research project to another.
3. Verification, validation and cleaning of data
4. Model, theories or hypothesis generation
5. Validation of model
6. Drawing analysis inferences

Let’s discuss a couple of practical examples to get a feel of what we are talking about. In clinical trials, for example, a team of new drug developers might be interested in the study of drug intake and measurable physiological effects like weight loss, the efficacy of a particular drug in preventing a disease in humans and so on. Another example can be a structured social media survey on what is the general perception of section business professionals on the effectiveness of big data in solving their supply chain problems. The day-to-day weather prediction is also based upon the collection of vast amounts of data on the parameters like temperature, concentration of dust particles and other gases, and so on.

A new book that makes modelling and applying many other statistical methods very easy

I and coauthor Venkat Reddy started working on a book titled Practical Business Analytics Using SAS: A Hands-on Guide. We spent a couple years looking at books on business analytics and predictive modeling. Some of them were really good. But most of them were too intense and deep on the theory and mathematics of statistical algorithms, which are an integral part of this subject. Some people like books that take that tack, but most practitioners—even those in the industry—don’t have the deep background in the math required or the interest in learning it. Working professionals, particularly newcomers to the field of business analytics, are not very comfortable with the deep theoretical treatment of statistical algorithms generally provided in most of the books available on analytics. The market need we discerned, therefore, was to simplify the presentation of algorithms for professionals who don’t need to know the details to succeed in their work. Besides, once introduced to the subject, one can always refer to the advanced texts on statistics if such academic rigor is required. The good news is that today’s analytics software, like SAS, is designed to do most of the math. Thus, we strongly felt there was a need for a book like this one, which takes the power of the software into account and, at the same time, simplifies the mathematical concepts involved in the process. With this motivation in mind, we started our work and strongly feel we have been successful in showing you how to use SAS to perform common analytical procedures while providing the basic knowledge of statistics required. The book keeps the theoretical part as simple as possible yet uses numerous real business scenarios to explain the concepts and the way they are used in the industry. Venkat’s working experience with the world’s leading banks and his vast experience working with students as an analytics trainer has come in handy in designing the case studies and examples used in this book.

Here is the content of this book, titled, Practical Business Analytics Using SAS

About the Authors ...................................................................................................xix

Acknowledgments ..................................................................................................xxi

Preface .................................................................................................................xxiii

■ Part 1: Basics of SAS Programming for Analytics .............................. 1

■ Chapter 1: Introduction to Business Analytics and Data Analysis Tools ...............3

■ Chapter 2: SAS Introduction ................................................................................29

■ Chapter 3: Data Handling Using SAS ..................................................................55

■ Chapter 4: Important SAS Functions and Procs .................................................. 95

■ Part 2: Using SAS for Business Analytics ..................................................... 145

■ Chapter 5: Introduction to Statistical Analysis .................................................... 147

■ Chapter 6: Basic Descriptive Statistics and Reporting in SAS ........................... 165

■ Chapter 7: Data Exploration, Validation, and Data Sanitization ........................ .197

■ Chapter 8: Testing of Hypothesis ........................................................................261

■ Chapter 9: Correlation and Linear Regression ................................................... 295

■ Chapter 10: Multiple Regression Analysis .......................................................... 351

■ Chapter 11: Logistic Regression ......................................................................... 401

■ Chapter 12: Time-Series Analysis and Forecasting ............................................ 441

■ Chapter 13: Introducing Big Data Analytics ...................................................... ..509

Index ..................................................................................................................... ..541

You can buy this book right now at Amazon. Reviews and suggestions are welcome at shailendrakadre@gmail.com

http://www.amazon.com/Practical-Business-Analytics-Using-Hands/dp/1484200446

http://businessanalyticsbykadre.blogspot.in/2015/02/big-data-versus-conventional-business.htmlhttp://www.slideshare.net/21_venkat/data-sets-practical-business-analytics-using-sas