03808nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072001400183072002300197072001500220072001300235100007800248245016300326250001800489264006900507300006500576336002600641337002600667338003600693347002400729505094200753520120701695650001802902650001602920650002402936650002702960650007102987650001603058650005003074710003403124773002603158776003603184776003603220776003603256856004603292978-3-031-42555-4DE-He21320251030111459.0cr nn 008mamaa240304s2024    sz |    s    |||| 0|eng d  a97830314255547 a10.1007/978-3-031-42555-42doi 4aQA276-280 7aPBT2bicssc 7aK2bicssc 7aBUS0610002bisacsh 7aPBT2thema 7aK2thema1 aFraser, Cynthia.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aBusiness Statistics for Competitive Advantage with Excel and JMPh[electronic resource] :bBasics, Model Building, Simulation, and Cases /cby Cynthia Fraser.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXI, 285 p. 375 illus., 69 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aChapter 1. Statistics for Decision Making and Competitive Advantage -- Chapter 2. Describing Your Data -- Chapter 3, Hypothesis Tests and Confidence Intervals to Infer Population Characteristics and Differences -- Chapter 4. Simulation to Infer Future Performance Levels Given Assumptions -- Chapter 5. Simple Regression -- Chapter 6. Finance Application: Portfolio Analysis with a Market Index as a Leading Indicator in Simple Linear Regression -- Chapter 7. Indicator Variables -- Chapter 8. Presenting Statistical Analysis Results to Management -- Chapter 9. Nonlinear Regression Models -- Chapter 10. Logit Regression for Bounded Dependent Variables -- Chapter 11. Building Multiple Regression Models -- Chapter 12. Model Building and Forecasting with Multicollinear Time Series -- Chapter 13. Association Between Two Categorical Variables: Contingency Analysis with Chi Square -- Chapter 14. Conjoint Analysis and Experimental Data.  aThis book is the latest title of the popular Excel textbook; redesigned, while including interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. How can performance outcome drivers be identified? How can performance outcomes be forecast? Use of regression, conjoint analysis, Monte Carlo simulation provide answers and solutions for specific scenarios. Students learn to build models, produce statistics, and translate results into implications for decision makers. The text features new and updated examples and assignments, and each chapter discusses a focal case from the business world which can be analyzed using the statistical strategies and software provided in the text. Paralleling recent interest in climate change and sustainability, new case studies concentrate on issues such as the impact of drought on business, automobile emissions, and sustainable package goods. The book continues its coverage of inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and JMP. 0aStatistics . 0aManagement. 0aMarketing research. 0aBusiness intelligence.14aStatistics in Business, Management, Economics, Finance, Insurance.24aManagement.24aMarket Research and Competitive Intelligence.2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303142554708iPrinted edition:z978303142556108iPrinted edition:z978303142557840uhttps://doi.org/10.1007/978-3-031-42555-4