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Introductory Business Statistics 2e

Introductory statistics with a business lens: descriptive statistics, probability, distributions, confidence intervals, hypothesis tests, ANOVA, and regression, applied to finance, marketing, and operations data. The exercises practice turning business data into decisions you can defend.

Introductory Business Statistics 2e

856 exercises62 sections

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Sections

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Sampling and Data

54

1.1 Definitions of Statistics, Probability, and Key Terms13

1.2 Data, Sampling, and Variation in Data and Sampling27

1.3 Levels of Measurement12

1.4 Experimental Design and Ethics2

Descriptive Statistics

93

2.1 Display Data13

2.2 Measures of the Location of the Data22

2.3 Measures of the Center of the Data11

2.4 Sigma Notation and Calculating the Arithmetic Mean12

2.5 Geometric Mean13

2.6 Skewness and the Mean, Median, and Mode5

2.7 Measures of the Spread of the Data17

Probability Topics

133

3.1 Terminology26

3.2 Independent and Mutually Exclusive Events27

3.3 Two Basic Rules of Probability31

3.4 Contingency Tables and Probability Trees27

3.5 Venn Diagrams22

Discrete Random Variables

76

4.1 Hypergeometric Distribution8

4.2 Binomial Distribution17

4.3 Geometric Distribution18

4.4 Poisson Distribution24

Continuous Random Variables

44

5.1 Properties of Continuous Probability Density Functions5

5.2 The Uniform Distribution17

5.3 The Exponential Distribution22

The Normal Distribution

55

6.1 The Standard Normal Distribution25

6.2 Using the Normal Distribution4

6.3 Estimating the Binomial with the Normal Distribution26

The Central Limit Theorem

61

7.1 The Central Limit Theorem for Sample Means6

7.2 Using the Central Limit Theorem25

7.3 The Central Limit Theorem for Proportions13

7.4 Finite Population Correction Factor17

Confidence Intervals

73

8.1 A Confidence Interval When the Population Standard Deviation Is Known or Large Sample Size3

8.2 A Confidence Interval When the Population Standard Deviation Is Unknown and Small Sample Case15

8.3 A Confidence Interval for A Population Proportion27

8.4 Calculating the Sample Size n: Continuous and Binary Random Variables28

Hypothesis Testing with One Sample

49

9.1 Null and Alternative Hypotheses7

9.2 Outcomes and the Type I and Type II Errors10

9.3 Probability Distribution Needed for Hypothesis Testing7

9.4 Full Hypothesis Test Examples25

Hypothesis Testing with Two Samples

75

10.1 Comparing Two Independent Population Means32

10.2 Cohen's Standards for Small, Medium, and Large Effect Sizes2

10.3 Test for Differences in Means: Assuming Equal Population Variances1

10.4 Comparing Two Independent Population Proportions15

10.5 Two Population Means with Known Standard Deviations11

10.6 Matched or Paired Samples14

The Chi-Square Distribution

70

11.1 Facts About the Chi-Square Distribution4

11.2 Test of a Single Variance17

11.3 Goodness-of-Fit Test18

11.4 Test of Independence19

11.5 Test for Homogeneity7

11.6 Comparison of the Chi-Square Tests5

F Distribution and One-Way ANOVA

40

12.1 Test of Two Variances12

12.2 One-Way ANOVA3

12.3 The F Distribution and the F-Ratio13

12.4 Facts About the F Distribution12

Linear Regression and Correlation

33

13.1 The Correlation Coefficient r10

13.2 Testing the Significance of the Correlation Coefficient2

13.3 Linear Equations7

13.4 The Regression Equation3

13.5 Interpretation of Regression Coefficients: Elasticity and Logarithmic Transformation3

13.6 Predicting with a Regression Equation6

13.7 How to Use Microsoft Excel® for Regression Analysis2

Adapted from Introductory Business Statistics 2e © 2023 Rice University. Licensed under CC BY 4.0. Source: Introductory Business Statistics 2e. Imported at revision 50ec917.