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020 _a9783031425554
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024 7 _a10.1007/978-3-031-42555-4
_2doi
050 4 _aQA276-280
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072 7 _aK
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072 7 _aBUS061000
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_2thema
100 1 _aFraser, Cynthia.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_972386
245 1 0 _aBusiness Statistics for Competitive Advantage with Excel and JMP
_h[electronic resource] :
_bBasics, Model Building, Simulation, and Cases /
_cby Cynthia Fraser.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXI, 285 p. 375 illus., 69 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _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.
520 _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.
650 0 _aStatistics .
_965982
650 0 _aManagement.
_9324
650 0 _aMarketing research.
_957888
650 0 _aBusiness intelligence.
_957215
650 1 4 _aStatistics in Business, Management, Economics, Finance, Insurance.
_969738
650 2 4 _aManagement.
_9324
650 2 4 _aMarket Research and Competitive Intelligence.
_968642
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031425547
776 0 8 _iPrinted edition:
_z9783031425561
776 0 8 _iPrinted edition:
_z9783031425578
856 4 0 _uhttps://doi.org/10.1007/978-3-031-42555-4
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c58093
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