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Introductory Statistics 2e

The classic college introduction to statistics: sampling, descriptive statistics, probability, distributions, the Central Limit Theorem, confidence intervals, hypothesis testing, chi-square, regression, and ANOVA. The exercises practice the full path from raw data to a defensible statistical conclusion.

Introductory Statistics 2e

816 exercises58 sections

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Sections

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Sampling and Data

71

1.1 Definitions of Statistics, Probability, and Key Terms15

1.2 Data, Sampling, and Variation in Data and Sampling39

1.3 Frequency, Frequency Tables, and Levels of Measurement9

1.4 Experimental Design and Ethics8

Descriptive Statistics

58

2.1 Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs4

2.2 Histograms, Frequency Polygons, and Time Series Graphs6

2.3 Measures of the Location of the Data17

2.5 Measures of the Center of the Data10

2.6 Skewness and the Mean, Median, and Mode5

2.7 Measures of the Spread of the Data15

Probability Topics

91

3.1 Terminology25

3.2 Independent and Mutually Exclusive Events13

3.3 Two Basic Rules of Probability27

3.4 Contingency Tables19

3.5 Tree and Venn Diagrams7

Discrete Random Variables

83

4.1 Probability Distribution Function (PDF) for a Discrete Random Variable10

4.2 Mean or Expected Value and Standard Deviation20

4.3 Binomial Distribution17

4.4 Geometric Distribution10

4.5 Hypergeometric Distribution8

4.6 Poisson Distribution18

Continuous Random Variables

43

5.1 Continuous Probability Functions5

5.2 The Uniform Distribution17

5.3 The Exponential Distribution21

The Normal Distribution

50

6.1 The Standard Normal Distribution31

6.2 Using the Normal Distribution19

The Central Limit Theorem

57

7.1 The Central Limit Theorem for Sample Means (Averages)13

7.2 The Central Limit Theorem for Sums19

7.3 Using the Central Limit Theorem25

Confidence Intervals

66

8.1 A Single Population Mean using the Normal Distribution22

8.2 A Single Population Mean using the Student t Distribution16

8.3 A Population Proportion28

Hypothesis Testing with One Sample

63

9.1 Null and Alternative Hypotheses7

9.2 Outcomes and the Type I and Type II Errors8

9.3 Probability Distribution Needed for Hypothesis Testing7

9.4 Rare Events, the Sample, Decision and Conclusion8

9.5 Additional Information and Full Hypothesis Test Examples33

Hypothesis Testing with Two Samples

82

10.1 Two Population Means with Unknown Standard Deviations34

10.2 Two Population Means with Known Standard Deviations11

10.3 Comparing Two Independent Population Proportions21

10.4 Matched or Paired Samples16

The Chi-Square Distribution

70

11.1 Facts About the Chi-Square Distribution4

11.2 Goodness-of-Fit Test16

11.3 Test of Independence19

11.4 Test for Homogeneity10

11.5 Comparison of the Chi-Square Tests5

11.6 Test of a Single Variance16

Linear Regression and Correlation

43

12.1 Linear Equations9

12.2 Scatter Plots3

12.3 The Regression Equation5

12.4 Testing the Significance of the Correlation Coefficient1

12.5 Prediction14

12.6 Outliers11

F Distribution and One-Way ANOVA

39

13.1 One-Way ANOVA5

13.2 The F Distribution and the F-Ratio9

13.3 Facts About the F Distribution14

13.4 Test of Two Variances11

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