A user's guide to business analytics / Ayanendranath Basu, Srabashi Basu.
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Item type | Current library | Call number | Copy number | Status | Notes | Date due | Barcode |
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Female Library | HD38.7 .B37 2016 (Browse shelf (Opens below)) | 1 | Available | STACKS | 51952000212003 | |
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Main Library | HD38.7 .B37 2016 (Browse shelf (Opens below)) | 1 | Available | STACKS | 51952000212010 |
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A User's Guide to Business Analytics provides a comprehensive discussion of statistical methods useful to the business analyst. Methods are developed from a fairly basic level to accommodate readers who have limited training in the theory of statistics. A substantial number of case studies and numerical illustrations using the R-software package are provided for the benefit of motivated beginners who want to get a head start in analytics as well as for experts on the job who will benefit by using this text as a reference book. The book is comprised of 12 chapters. The first chapter focuses on business analytics, along with its emergence and application, and sets up a context for the whole book. The next three chapters introduce R and provide a comprehensive discussion on descriptive analytics, including numerical data summarization and visual analytics. Chapters five through seven discuss set theory, definitions and counting rules, probability, random variables, and probability distributions, with a number of business scenario examples. These chapters lay down the foundation for predictive analytics and model building. -- Provided by publisher.
What is analytics? -- Intorducing R -- An analytics software -- Reporting data -- Statistical graphics and visual analytics -- Probability -- Random variables and probability distributions -- Continuous random variables -- Statistical inference -- Regression for predictive model building -- Decision trees -- Data mining and multivariate methods -- Modeling time series data for forecasting.
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