【簡介】 ●Decision Dilemmas: Each course section is introduced with a real-world business vignette that presents a dilemma and related managerial or statistical questions. Solutions to these questions require the use of techniques presented in the section. A Decision Dilemma Solved feature concludes each section, giving students the opportunity to answer and discuss each question presented at the beginning of the section. ●Thinking Critically About Statistics in Business Today Exercises: Each course section features one or several of these exercises that give real-life examples of how the statistics presented in the section apply in the business world today. ●Databases: Twenty databases representing several industries including banking, consumer spending, energy, environmental, finance, manufacturing, healthcare, market research, retailing, stocks, and more provide additional opportunities for students to apply the statistics presented in each chapter. ●Big Data Cases engage students with variables, samples, and data. With data from the American Hospital Association, these cases enable students to solve and perform a number of data tasks that are practical for the course and future careers. ●Ethical Considerations: This feature in each course section integrates the topic of ethics with applications of business statistics. ●Demonstration Problems: Virtually every section of every chapter contains demonstration problems. A demonstration problem contains both an example problem and its solution and is used as an additional pedagogical tool to supplement explanations and examples. ●900+ Practice Problems: A treasury of practice problems are available in this course. 【目錄】 1 Introduction to Statistics and Business Analytics 2 Visualizing Data with Charts and Graphs 3 Descriptive Statistics 4 Probability 5 Discrete Random Variables and Their Probability Distributions 6 Continuous Random Variables and Normal Distributions 7 Sampling and Sampling Distributions 8 Statistical Inference: Estimation for Single Populations 9 Statistical Inference: Hypothesis Testing for Single Populations 10 Statistical Inference About Two Populations 11 Analysis of Variance and Design of Experiments 12 Simple Regression Analysis and Correlation 13 Multiple Regression Analysis 14 Building Multiple Regression Models 15 Time-Series Forecasting and Index Numbers 16 Analysis of Categorical Data 17 Nonparametric Statistics 18 Statistical Quality Control 19 Decision Analysis