Discovering Business Statistics, 2nd Edition

2.1 Data and Decision Making

2.2 Big Data and Business Analytics

2.3 Data Classifications

2.4 Time Series Data and Cross-Sectional Data

3.1 Frequency Distributions

3.2 Displaying Qualitative Data

3.3 Constructing Frequency Distributions for Quantitative Data

3.4 Graphical Displays of Quantitative Data

3.5 Analyzing Graphs

4.1 Measures of Location

4.2 Measures of Dispersion

4.3 Measures of Relative Position

4.4 Data Subsetting

4.5 Analyzing Grouped Data

4.6 Proportions

4.7 Measures of Association Between Two Variables

5.1 Introduction to Probability

5.2 Laws of Probability

5.3 Conditional Probability

5.4 Independence

5.5 Bayes' Theorem

5.6 Counting Techniques

6.1 Types of Random Variables

6.2 Discrete Random Variables

6.3 The Discrete Uniform Distribution

6.4 The Binomial Distribution

6.5 The Poisson Distribution

6.6 The Hypergeometric Distribution

7.1 The Uniform Distribution

7.2 The Normal Distribution

7.3 Assessing Normality Graphically

7.4 The Standard Normal Distribution

7.5 Approximations to Other Distributions

8.1 Random Samples and Sampling Distributions

8.2 The Distribution of the Sample Mean and the Central Limit Theorem

8.3 The Distribution of the Sample Proportion

8.4 Sampling Methods

9.1 Estimating the Population Mean, Sigma Known

9.2 Estimating the Population Mean, Sigma Unknown

9.3 Estimating the Population Proportion

9.4 Estimating the Population Standard Deviation or Variance

10.1 Introduction to Hypothesis Testing

10.2 Testing a Hypothesis about a Population Mean, Sigma Known

10.3 Testing a Hypothesis about a Population Mean, Sigma Unknown

10.4 The Relationship Between Confidence Interval Estimation and Hypothesis Testing

10.5 Testing a Hypothesis about a Population Proportion

10.6 Testing a Hypothesis about a Population Variance

11.1 Comparing Two Population Means, Sigma 1 and Sigma 2 Known

11.2 Comparing Two Population Means, Sigma 1 and Sigma 2 Unknown

11.3 Paired Difference Test

11.4 Comparing Two Population Proportions

11.5 Comparing Two Population Variances

12.1 Introduction to Analysis of Variance (ANOVA)

12.2 Assumptions in an ANOVA Test

12.3 The F-Distribution and the F-Test

12.4 Multiple Comparison Procedures

12.5 Two-Way ANOVA: The Randomized Block Design

12.6 Two-Way ANOVA: The Factorial Design

13.1 The Simple Linear Regression Model

13.2 Residual Analysis

13.3 Evaluating the Fit of the Linear Regression Model

13.4 Fitting a Linear Time Trend

13.5 Inference Concerning the Slope

13.6 Inference Concerning the Model's Prediction

14.1 The Multiple Regression Model

14.2 The Coefficient of Determination and Adjusted R^2

14.3 Inference Concerning the Multiple Regression Model and Its Coefficients

14.4 Inference Concerning the Model's Prediction

14.5 Models with Qualitative Independent Variables

14.6 Additional Topics in Multiple Regression

15.1 Time Series Components

15.2 Moving Averages

15.3 Exponential Smoothing Techniques

15.4 Forecast Accuracy

15.5 Seasonality

16.1 The Chi-Square Distribution

16.2 The Chi-Square Test for Goodness of Fit

16.3 The Chi-Square Test for Association

17.1 The Sign Test

17.2 The Wilcoxon Signed-Rank Test

17.3 The Wilcoxon Rank-Sum Test

17.4 The Rank Correlation Test

17.5 The Runs Test for Randomness

17.6 The Kruskal-Wallis Test

18.1 Basic Charts and Diagrams Used in Quality Control

18.2 Basic Concepts

18.3 Monitoring with x-Bar and R Charts

18.4 Monitoring with a p Chart

A.1 Name that Distribution

A.2 Direct Mail

A.3 Type II Errors

A.4 Games of Chance

• Examples
• Example A4.1: Expected Value
• Example A4.2: Expected Value
• Example A4.3: Expected Value