James R. Evans (Author)
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For undergraduate or graduate business students.
A balanced and holistic approach to business analytics
Business Analytics teaches the fundamental concepts of modern business analytics and provides vital tools in understanding how data analysis works in today’s organizations. Author James Evans takes a fair and comprehensive, approach, examining business analytics from both descriptive and predictive perspectives. Students learn how to apply basic principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. And included access to commercial grade analytics software gives students real-world experience and career-focused value. As such, the 3rd Edition has gone through an extensive revision and now relies solely on Excel, enhancing students’ skills in the program and basic understanding of fundamental concepts. Additionally, Analytic Solver can now be found in online supplements to accommodate any new software updates, so students are prepared to use these same tools when they graduate.
Also available with MyLab Business Statistics
By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student. For example, new Excel and StatCrunch Projects help students develop business decision-making skills.
Note: You are purchasing a standalone product; MyLab Business Statistics does not come packaged with this content. Students, if interested in purchasing this title with MyLab Business Statistics, ask your instructor to confirm the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information.
013586027X / 9780135860274
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Book Table: Business Analytics:
|How to trust? ask for sample.|
|authors||James R. Evans|
|description||Introduction to business analytics -- Analytics on spreadsheets -- Visualizing and exploring data -- Descriptive statistical measures -- Probability distributions and data modeling -- Sampling and estimation -- Statistical inference -- Trendlines and regression analysis -- Forecasting techniques -- Introduction to data mining -- Spreadsheet modeling and analysis -- Monte Carlo simulation and risk analysis -- Linear optimization -- Applications of linear optimization -- Integer optimization -- Decision analysis|
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