Thistitle is a Pearson Global Edition. The Editorial team at Pearson has workedclosely with educators around the world to include content which is especiallyrelevant to students outside the United States. For courses in Introductory Business Statistics. Real data. Real decisions. Real business. Statistics for Business and Economics byMcClave, Benson, and Sincich introduces statistics in the context ofcontemporary business. Inference isemphasized, with extensive coverage of data collection and analysisas needed to evaluate the reported results of statistical studies and make gooddecisions. The…mehr
Thistitle is a Pearson Global Edition. The Editorial team at Pearson has workedclosely with educators around the world to include content which is especiallyrelevant to students outside the United States. For courses in Introductory Business Statistics. Real data. Real decisions. Real business. Statistics for Business and Economics byMcClave, Benson, and Sincich introduces statistics in the context ofcontemporary business. Inference isemphasized, with extensive coverage of data collection and analysisas needed to evaluate the reported results of statistical studies and make gooddecisions. The authors apply concepts with realdata. Technology is used to help students develop statisticalthinking and understand the assessment of credibilityand the value of the inferences made from data GÇö both bythose who consume and by those who produce them. The 14thEdition continues to highlight the discussion of ethical, datadriven decision making.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Jim McClave is currently President and CEO ofInfo Tech, Inc., a statistical consulting and software development firm with aninternational clientele. He is also a Courtesy Professor ofStatistics at the University of Florida, where he was a full-time member of thefaculty for over 20 years. Dr. Terry Sincich obtained his PhD inStatistics from the University of Florida in 1980. He is a ProfessorEmeritus of the Information Systems & Decision SciencesDepartment at the University of South Florida in Tampa, where hewas responsible for teaching basic statistics to all undergraduates, aswell as advanced statistics to all doctoral candidates, in the College ofBusiness Administration. He has published articles in such journals asthe Journal of the American Statistical Association, InternationalJournal of Forecasting, Academy of Management Journal,and Auditing: A Journal of Practice & Theory.Dr. Sincich is a co-author of the texts: Statistics, Statisticsfor Business & Economics, Statistics for Engineering & theSciences, and A Second Course in Statistics: Regression Analysis.
Inhaltsangabe
1. Statistics, Data, and Statistical Thinking 2. Methods for Describing Sets of Data 3. Probability 4. Random Variables and Probability Distributions 5. Sampling Distributions 6. Inferences Based on a Single Sample: Estimation with ConfidenceIntervals 7. Inferences Based on a Single Sample: Tests of Hypotheses 8. Inferences Based on Two Samples: Confidence Intervals and Testsof Hypotheses 9. Design of Experiments and Analysis of Variance 10. Categorical Data Analysis 11. Simple Linear Regression 12. Multiple Regression and Model Building 13. Methods for Quality Improvement: Statistical Process Control(Available Online) 14. Time Series: Descriptive Analyses, Models, and Forecasting(Available Online) 15. Nonparametric Statistics (Available Online)
Appendix A: Summation Notation Appendix B: Basic Counting Rules Appendix C: Calculation Formulas for Analysis of Variance C.1 Formulas for the Calculationsin the Completely Randomized Design C.2 Formulas for the Calculationsin the Randomized Block Design C.3 Formulas for the Calculationsfor a Two-Factor Factorial Experiment C.4 Tukey's Multiple ComparisonsProcedure (Equal Sample Sizes) C.5 Bonferroni MultipleComparisons Procedure (Pairwise Comparisons) C.6 Scheffé's MultipleComparisons Procedure (Pairwise Comparisons) Appendix D: Tables
1. Statistics, Data, and Statistical Thinking 2. Methods for Describing Sets of Data 3. Probability 4. Random Variables and Probability Distributions 5. Sampling Distributions 6. Inferences Based on a Single Sample: Estimation with ConfidenceIntervals 7. Inferences Based on a Single Sample: Tests of Hypotheses 8. Inferences Based on Two Samples: Confidence Intervals and Testsof Hypotheses 9. Design of Experiments and Analysis of Variance 10. Categorical Data Analysis 11. Simple Linear Regression 12. Multiple Regression and Model Building 13. Methods for Quality Improvement: Statistical Process Control(Available Online) 14. Time Series: Descriptive Analyses, Models, and Forecasting(Available Online) 15. Nonparametric Statistics (Available Online)
Appendix A: Summation Notation Appendix B: Basic Counting Rules Appendix C: Calculation Formulas for Analysis of Variance C.1 Formulas for the Calculationsin the Completely Randomized Design C.2 Formulas for the Calculationsin the Randomized Block Design C.3 Formulas for the Calculationsfor a Two-Factor Factorial Experiment C.4 Tukey's Multiple ComparisonsProcedure (Equal Sample Sizes) C.5 Bonferroni MultipleComparisons Procedure (Pairwise Comparisons) C.6 Scheffé's MultipleComparisons Procedure (Pairwise Comparisons) Appendix D: Tables
Answers to Selected Exercises Index Credits
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