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商品簡介
1. A modern, practical and unique framework for teaching an introductory course in Business Statistics.
2. Employs realistic examples, continuing case studies and a business improvement theme to teach the material.
3. Features more concise and lucid explanations, an improved topic flow and a sensible use of the best and most compelling examples.
2. Employs realistic examples, continuing case studies and a business improvement theme to teach the material.
3. Features more concise and lucid explanations, an improved topic flow and a sensible use of the best and most compelling examples.
作者簡介
作者:Bruce L. Bowerman
現職:Miami University
作者:Anne M. Drougas
現職:Dominican University
作者:William M. Duckworth
現職:Creighton University
作者:Amy G. Froelich
現職:Iowa State University
作者:Ruth M. Hummel
現職:JMP
作者:Kyle B. Moninger
現職:Bowling Green State University
作者:Patrick J. Schur
現職:Miami University
現職:Miami University
作者:Anne M. Drougas
現職:Dominican University
作者:William M. Duckworth
現職:Creighton University
作者:Amy G. Froelich
現職:Iowa State University
作者:Ruth M. Hummel
現職:JMP
作者:Kyle B. Moninger
現職:Bowling Green State University
作者:Patrick J. Schur
現職:Miami University
目次
Ch 1 An Introduction to Business Statistics and Analytics
Ch 2 Descriptive Statistics and Analytics: Tabular and Graphical Methods
Ch 3 Descriptive Statistics and Analytics: Numerical Methods
Ch 4 Probability and Probability Models
Ch 5 Predictive Analytics I: Trees, k-Nearest Neighbors, Naive Bayes’, and Ensemble Estimates
Ch 6 Discrete Random Variables
Ch 7 Continuous Random Variables
Ch 8 Sampling Distributions
Ch 9 Confidence Intervals
Ch10 Hypothesis Testing
Ch11 Statistical Inferences Based on Two Samples
Ch12 Experimental Design and Analysis of Variance
Ch13 Chi-Square Tests
Ch14 Simple Linear Regression Analysis
Ch15 Multiple Regression and Model Building
Ch16 Predictive Analytics II: Logis¬tic Regression, Discriminate Analysis, and Neural Networks
Ch17 Time Series Forecasting and Index Numbers
Ch18 Nonparametric Methods
Ch19 Decision Theory
Ch20 (Online) Process Improvement Using Control Charts for Website
Appendix A Statistical Tables
Appendix B (Online) Chapter by Chapter MegaStat
Ch 2 Descriptive Statistics and Analytics: Tabular and Graphical Methods
Ch 3 Descriptive Statistics and Analytics: Numerical Methods
Ch 4 Probability and Probability Models
Ch 5 Predictive Analytics I: Trees, k-Nearest Neighbors, Naive Bayes’, and Ensemble Estimates
Ch 6 Discrete Random Variables
Ch 7 Continuous Random Variables
Ch 8 Sampling Distributions
Ch 9 Confidence Intervals
Ch10 Hypothesis Testing
Ch11 Statistical Inferences Based on Two Samples
Ch12 Experimental Design and Analysis of Variance
Ch13 Chi-Square Tests
Ch14 Simple Linear Regression Analysis
Ch15 Multiple Regression and Model Building
Ch16 Predictive Analytics II: Logis¬tic Regression, Discriminate Analysis, and Neural Networks
Ch17 Time Series Forecasting and Index Numbers
Ch18 Nonparametric Methods
Ch19 Decision Theory
Ch20 (Online) Process Improvement Using Control Charts for Website
Appendix A Statistical Tables
Appendix B (Online) Chapter by Chapter MegaStat
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