• 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.
• EXPANDED 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.
• NEW Big Data Case: Using data from the American Hospital Association, each chapter contains an activity asking students to perform several tasks using variables, samples, and data.
• NEW Visualizing Time-Series Data Section: helps students use historical data with measures taken over time to predict what might happen in the future.
• Ethical Considerations: This feature in each course section integrates the topic of ethics with applications of business statistics.
• Tree Taxonomy Diagrams: These diagrams illustrate the connection between topics and techniques and the ability to see the big picture of inferential statistics.
• Section Reorganization Options: This course was designed to allow for both one- and two-semester coverage.
• 900+ Practice Problems: A treasury of practice problems are available in this course.
1 Introduction to Statistics and Business Analytics
2 Visualizing Data with Charts and Graphs
3 Descriptive Statistics
5 Discrete Distributions
6 Continuous Distributions
7 Sampling and Sampling Distributions
8 Statistical Inference: Estimation for Single Populations
9 Statistical Inference: Hypothesis Testing for Single Populations
10 Statistical Inferences 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
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