# Alignment: OpenStax • Introductory Business Statistics

• Chapter 1 Sampling and Data
• 1.1 Definitions of Statistics, Probability, and Key Terms
• 1.2 Data, Sampling, and Variation in Data and Sampling
• 1.3 Levels of Measurement
• 1.4 Experimental Design and Ethics
• Chapter 2 Descriptive Statistics
• 2.1 Display Data
• 2.2 Measures of the Location of the Data
• 2.3 Measures of the Center of the Data
• 2.4 Sigma Notation and Calculating the Arithmetic Mean
• 2.5 Geometric Mean
• 2.6 Skewness and the Mean, Median, and Mode
• 2.7 Measures of the Spread of the Data
• Chapter 3 Probability Topics
• 3.1 Terminology
• 3.2 Independent and Mutually Exclusive Events
• 3.3 Two Basic Rules of Probability
• 3.4 Contingency Tables and Probability Trees
• 3.5 Venn Diagrams
• Chapter 4 Discrete Random Variables
• 4.1 Hypergeometric Distribution
• 4.2 Binomial Distribution
• 4.3 Geometric Distribution
• 4.4 Poisson Distribution
• Chapter 5 Continuous Random Variables
• 5.1 Properties of Continuous Probability Density Functions
• 5.2 The Uniform Distribution
• 5.3 The Exponential Distribution
• Chapter 6 The Normal Distribution
• 6.1 The Standard Normal Distribution
• 6.2 Using the Normal Distribution
• 6.3 Estimating the Binomial with the Normal Distribution
• Chapter 7 The Central Limit Theorem
• 7.1 The Central Limit Theorem for Sample Means
• 7.2 Using the Central Limit Theorem
• 7.3 The Central Limit Theorem for Proportions
• 7.4 Finite Population Correction Factor
• Chapter 8 Confidence Intervals
• 8.1 A Confidence Interval for a Population Standard Deviation, Known or Large Sample Size
• 8.2 A Confidence Interval for a Population Standard Deviation Unknown, Small Sample Case
• 8.3 A Confidence Interval for a Population Proportion
• 8.4 Calculating the Sample Size 𝑛: Continuous and Binary Random Variables
• Chapter 9 Hypothesis Testing with One Sample
• 9.1 Null and Alternative Hypotheses
• 9.2 Outcomes and the Type I and Type II Errors
• 9.3 Distribution Needed for Hypothesis Testing
• 9.4 Full Hypothesis Test Examples
• Chapter 10 Hypothesis Testing with Two Samples
• 10.1 Comparing Two Independent Population Means
• 10.2 Cohen’s Standards for Small, Medium, and Large Effect Sizes
• 10.3 Test for Differences in Means: Assuming Equal Population Variances
• 10.4 Comparing Two Independent Population Proportions
• 10.5 Two Population Means with Known Standard Deviations
• 10.6 Matched or Paired Samples
• Chapter 11 The Chi-Square Distribution
• 11.1 Facts about the Chi-Square Distribution
• 11.2 Test of a Single Variance
• 11.3 Goodness-of-Fit Test
• 11.4 Test of Independence
• 11.5 Test for Homogeneity
• 11.6 Comparison of the Chi-Square Tests
• Chapter 12 𝐹 Distribution and One-Way ANOVA
• 12.1 Test of Two Variances
• 12.2 One-Way ANOVA
• 12.3 The 𝐹 Distribution and the 𝐹-Ratio
• 12.4 Facts about the 𝐹 Distribution
• Chapter 13 Linear Regression and Correlation
• 13.1 The Correlation Coefficient 𝑟
• 13.2 Testing the Significance of the Correlation Coefficient
• 13.3 Linear Equations
• 13.4 The Regression Equation
• 13.5 Interpretation of Regression Coefficients: Elasticity and Logarithmic Transformation
• 13.6 Predicting with a Regression Equation
• 13.7 How to Use Microsoft Excel® for Regression Analysis
• Appendix A Statistical Tables
• Appendix B Mathematical Phrases, Symbols, and Formulas

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