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Applied Statistics in Business and Economics
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Applied Statistics in Business and Economics

Book Details

Format Hardback or Cased Book
ISBN-10 1260716287
ISBN-13 9781260716283
Publisher McGraw-Hill Education
Imprint McGraw-Hill Education
Country of Manufacture GB
Country of Publication GB
Publication Date Mar 11th, 2021
Weight 1,755 grams
Product Classification: Probability & statistics
Ksh 34,650.00
Publisher Out of Stock 0 in stock

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Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how.  The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics.  It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.
Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how.  The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics.  It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.

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