滿額折
Business Statistics and Analytics in Practice
- ISBN13：9781260287844
- 出版社：Mcgraw-Hill; Inc.
- 作者：Bruce L. Bowerman; Anne M. Drougas; William M. Duckworth; Amy G. Froelich; Ruth M. Hummel; Kyle B. Moninger; Patrick J. Schur
- 裝訂／頁數：平裝／906頁
- 規格：27.6cm*21.6cm*2.8cm (高/寬/厚)
- 重量：1646克
- 版次：9
- 出版日：2019/05/17
定 價：NT$ 1720 元
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作者簡介
目次
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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