By Ayanendranath Basu, Srabashi Basu
A User's consultant to enterprise Analytics offers a complete dialogue of statistical tools invaluable to the company analyst. tools are constructed from a pretty uncomplicated point to deal with readers who've restricted education within the conception of records. a considerable variety of case stories and numerical illustrations utilizing the R-software package deal are supplied for the advantage of encouraged newbies who are looking to get a head begin in analytics in addition to for specialists at the activity who will profit through the use of this article as a reference book.
The e-book is made out of 12 chapters. the 1st bankruptcy specializes in enterprise analytics, in addition to its emergence and alertness, and units up a context for the entire publication. the subsequent 3 chapters introduce R and supply a accomplished dialogue on descriptive analytics, together with numerical info summarization and visible analytics. Chapters 5 via seven speak about set thought, definitions and counting principles, likelihood, random variables, and chance distributions, with a couple of company state of affairs examples. those chapters lay down the basis for predictive analytics and version building.
Chapter 8 offers with statistical inference and discusses the commonest checking out techniques. Chapters 9 via twelve deal completely with predictive analytics. The bankruptcy on regression is kind of large, facing version improvement and version complexity from a user’s viewpoint. a brief bankruptcy on tree-based equipment places forth the most software parts succinctly. The bankruptcy on information mining is an efficient advent to the commonest computing device studying algorithms. The final bankruptcy highlights the function of alternative time sequence versions in analytics. In the entire chapters, the authors exhibit a few examples and case stories and supply directions to clients within the analytics field.
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Extra resources for A user’s guide to business analytics
Sample text
We have used only R for all the examples that are discussed in this book. For many of the illustrations, important parts of the codes are also provided along with the R output. In this chapter we provide a very brief glimpse into the working of R and indications as to where one should look for help in case one gets stuck. It is not possible to provide comprehensive guidance on R in a single chapter. Indeed, in this brief note we are not even able to scratch the surface of R functionalities. But a context setting for the very first users of R should be helpful.
There may also be a third step, where the modeling knowledge is applied in an optimum way to exert a greater control on the future. This is called prescriptive analytics. Most businesses, at least in India, have not matured to the stage where they are even able to take advantage of modeling. There is no dearth of data, but only a limited amount of information is being extracted, from which it is not possible to gain maximum knowledge. A vast majority of businesses are still sitting on a pile of expensive data but are making little use of it and running the business on gut feeling.
All of them are past or present students of the Indian Statistical Institute, or have been associated with the Institute in the capacity of project-related personnel. Dr. Das is currently a Professor at the Institute. We are grateful to all of them. We also gratefully acknowledge the support and cooperation received from the CRC colleagues including Ms. Aastha Sharma, Mr. Delroy Lowe, Ms. Robin Lloyd-Starkes, Mr. Alex Edwards and Mr. Gary Stallons. Mr. Shashi Kumar’s expert advise and assistance has helped us overcome the hurdles of typesestting in LATEX.