Discovering Statistics, 2nd Edition

2.1 - 2.4 The Reality of Conducting a Study

• Examples
• Example 2.1
• Example 2.2

2.5 - 2.6 Levels of Measurement

• Examples
• Example 2.4
• Example 2.5

3a Frequency Distributions

• Examples
• Example 3.1: Constructing a Frequency Distribution
• Example 3.2: A Model to Determine Virtual Security Practices
• Example 3.3
• Example 3.4
• Example 3.5
• Example 3.6

3b Graphical Displays of Data: Pie Charts and Bar Graphs

3c Graphical Displays of Data: Histograms, Polygons, Stem and Leaf Plots

• Examples
• Example 3.7
• Example 3.8
• Example 3.9
• Example 3.10
• Example 3.11

3d Analyzing Graphs

• Examples
• Example 3.12: Scaling of Graphs
• Example 3.13: Shapes of Graphs

4.1 - 4.3a Measures of Location

• Examples
• Example 4.1
• Example 4.2
• Example 4.3
• Example 4.4
• Example 4.5
• Example 4.6
• Example 4.7

4.1 - 4.3b Measures of Dispersion

• Examples
• Example 4.8
• Example 4.9
• Example 4.10
• Example 4.11

4.1 - 4.3c Constructing Samples

• Examples
• Example 4.12: Construct a Sample
• Example 4.13: Construct a Sample
• Example 4.14: Construct a Bimodal Sample
• Example 4.15: Adding a Sample Value
• Example 4.16: Adding a Sample Value
• Example 4.17: Adding a Sample Value
• Example 4.18: Construct a Sample

4.4 Measures of Relative Position

• Examples
• Example 4.19
• Example 4.20
• Example 4.22

4.5 - 4.10 Applying the Standard Deviation

• Examples
• Example 4.23
• Example 4.24
• Example 4.25
• Example 4.26
• Example 4.27

5.2 - 5.5 Scatter Plots and Correlation

• Examples
• Example 5.1

5.6 - 5.9 Fitting a Linear Model

• Examples
• Example 5.2

6.1 - 6.4 Classical Probability

• Examples
• Example 6.1
• Example 6.2
• Example 6.3
• Example 6.4

6.5 - 6.9 Probability Rules: Properties, the Complement, and Addition Rules

• Examples
• Example 6.5
• Example 6.6
• Example 6.7
• Example 6.8

6.10 - 6.11 Probability Rules: Independence, Multiplication Rules, and Conditional Probability

• Examples
• Example 6.9
• Example 6.10
• Example 6.11
• Example 6.12
• Example 6.13

6.12a Basic Counting Rules

• Examples
• Example 6.14
• Example 6.15
• Example 6.16
• Example 6.17
• Example 6.18
• Example 6.19
• Example 6.20
• Example 6.21

6.12b Additional Counting Techniques

• Examples
• Example 6.22: Calculating Probability Using Combinations
• Example 6.23: Calculating Probability Using Permutations
• Example 6.24: Using Numbers of Combinations with the Fundamental Counting Principle
• Example 6.25: Using Numbers of Combinations with the Fundamental Counting Principle

7.1 - 7.4 Discrete Random Variables

• Examples
• Example 7.1
• Example 7.2
• Example 7.3
• Example 7.4
• Example 7.5
• Example 7.6
• Example 7.7
• Example 7.8
• Example 7.9
• Example 7.10

7.7 The Binomial Distribution

• Examples
• Example 7.11
• Example 7.12
• Example 7.13
• Example 7.14

7.8 The Poisson Distribution

• Examples
• Example 7.15
• Example 7.16

7.9 The Hypergeometric Distribution

• Examples
• Example 7.17
• Example 7.18

8.3a Introduction to the Normal Curve

8.3b Reading a Normal Curve Table

• Examples
• Example 8.1
• Example 8.2
• Example 8.3

8.4a The Normal Distribution

• Examples
• Example 8.4
• Example 8.5
• Example 8.6
• Example 8.7

8.4b z - Transformations

• Examples
• Example 8.8: Finding the z-Value with a Given Area to Its Left
• Example 8.9: Finding the z-Value with a Given Area to Its Left
• Example 8.10: Finding the z-Value That Represents a Given Percentile
• Example 8.11: Finding the z-Value with a Given Area to Its Right
• Example 8.12: Finding the z-value with a given area between −z and z
• Example 8.13: Finding the z-Value with a Given Area in the Tails to the Left of −z and to the Right of z
• Example 8.16: Finding the Value of a Normally Distributed Random Variable That Represents a Given Percentile

8.5 Approximations to Other Distributions

• Examples
• Example 8.17
• Example 8.18
• Example 8.19
• Example 8.20

9.1 - 9.5 Random Samples and Sampling Distributions

• Examples
• Example 9.1

9.6 - 9.7 The Distribution of the Sample Mean and the Central Limit Theorem

• Examples
• Example 9.2
• Example 9.3
• Example 9.4

9.8 The Distribution of the Sample Proportion

• Examples
• Example 9.5
• Example 9.6

10.1 - 10.4 Interval Estimation of the Population Mean

• Examples
• Example 10.1
• Example 10.2

10.5a Student's t-Distribution

• Examples
• Example 10.3: Finding the Value of $t_{\alpha }$
• Example 10.4: Finding the Value of t Given the Area to the Right
• Example 10.5: Finding the Value of t Given the Area to the Left
• Example 10.6: Finding the Value of t Given the Area in Two Tails
• Example 10.7: Finding the Value of t Given Area between −t and t
• Example 10.8: Finding the Critical t-Value for a Confidence Interval

10.5b Interval Estimation of the Population Mean for a Normal Population with Sigma Unknown

• Examples
• Example 10.9
• Example 10.10

10.6 Precision and Sample Size

• Examples
• Example 10.11
• Example 10.12
• Example 10.13

10.7 - 10.9 Estimating Population Attributes

• Examples
• Example 10.14
• Example 10.15
• Example 10.16
• Example 10.17

11.1 - 11.3 Developing a Hypothesis and Reaching a Conclusion

• Examples
• Example 11.1
• Example 11.2
• Example 11.3
• Example 11.4

11.4a Hypothesis Testing Means (P Value)

• Examples
• Example 11.5: Formulating Hypotheses
• Example 11.6: Hypothesis Test Using Rejection Regions
• Example 11.7: P-Value for a One-Tailed Test
• Example 11.8: P-Value for a Two-Tailed Test
• Example 11.9: Conclusions Using P-Value
• Example 11.10: Hypothesis Test Using P-Value
• Example 11.11: Hypothesis Test Using P-Value

11.4b Hypothesis Testing Means (z Value)

• Examples
• Example 11.12
• Example 11.13

11.4c Hypothesis Testing Means (t Value)

• Examples
• Example 11.14
• Example 11.15

12.1a Hypothesis Testing Proportions (P Value)

• Examples
• Example 12.1: Formulating Hypotheses
• Example 12.2: Hypothesis Testing Using Rejection Regions
• Example 12.3: P-Value for a One-Tailed Test
• Example 12.4: P-Value for a Two-Tailed Test
• Example 12.5: Conclusions Using P-Value
• Example 12.6: Hypothesis Test Using P-Value
• Example 12.7: Hypothesis Test Using P-Value

12.1b Hypothesis Testing Proportions (z Value)

• Examples
• Example 12.8: Testing a Hypothesis about a Population Proportion
• Example 12.9: Testing a Hypothesis about a Population Proportion

12.2 Testing Hypothesis about a Population Variance

• Examples
• Example 12.10: Testing a Hypothesis Concerning a Population Variance

12.3a Comparing Two Means (Large Independent Samples)

• Examples
• Example 12.11: Performing a Hypothesis Test for Two Population Means

12.3b Comparing Two Means (Small Independent Samples)

• Examples
• Example 12.12

12.4 Paired Difference

• Examples
• Example 12.13

12.5 Comparing Two Population Proportions

• Examples
• Example 12.14

13.2 - 13.4 Regression Analysis I

• Examples
• Example 13.1
• Example 13.2
• Example 13.3
• Example 13.4
• Example 13.5
• Example 13.6

13.8a Inference Concerning the Coefficients of the Multiple Regression Model

• Examples
• Example 13.7
• Example 13.8
• Example 13.9

13.8b ANOVA Regression

14.2, 14.4 ANOVA

• Examples
• Example 14.1
• Example 14.2

15.2 Chi-Square Test for Goodness of Fit

• Examples
• Example 15.1

15.3 Chi-Square Test for Association Between Two Qualitative Variables

• Examples
• Example 15.2

17.3 Monitoring with an x-bar Chart

• Examples
• Example 17.1
• Example 17.2

17.4 Monitoring with an R Chart

• Examples
• Example 17.3

17.5 Monitoring with a p Chart

• Examples
• Example 17.4: p-Charts

A.1 The Process of a Statistical Study

• Examples
• Example A1.1: Identifying Population and Variables
• Example A1.2: Identifying Observational Studies and Experiments
• Example A1.3: Identifying Sampling Methods
• Example A1.4: Classifying Studies as Cross-Sectional or Longitudinal
• Example A1.5: Classifying Studies as Meta-Analysis or Case Study
• Example A1.6: Analyzing an Experiment

A.2 Games of Chance

• Examples
• Example A2.1: Expected Value
• Example A2.2: Expected Value
• Example A2.3: Expected Value

A.3 Name that Distribution

A.4 Comparing Two Means (Large, Independent Samples)

• Examples
• Example A4.1: Finding the Point Estimate and Margin of Error of a Confidence Interval for the Difference between Two Population Means (σ Known)
• Example A4.2: Constructing a Confidence Interval for the Difference between Two Population Means (σ Known)

A.5 Comparing Two Means (Small, Independent Samples)

• Examples
• Example A5.1: Confidence Intervals

A.6 Comparing Two Means (Dependent Samples)

• Examples
• Example A6.1: Calculating Paired Differences
• Example A6.2: Finding a Point Estimate for the Mean of the Paired Differences for Two Populations (σ Unknown, Dependent Samples)
• Example A6.3: Constructing a Confidence Interval for the Mean of the Paired Differences for Two Populations (σ Unknown, Dependent Samples)

A.7 Comparing Two Proportions (Large, Independent Samples)

• Examples
• Example A7.1: Calculating Sample Proportions and Verifying Sample Size Conditions
• Example A7.2: Constructing a Confidence Interval for the Difference between Two Population Proportions
• Example A7.3: Constructing a Confidence Interval for the Difference between Two Population Proportions

A.8 Comparing Two Population Variances

• Examples
• Example A8.1: Calculating the Point Estimate for Comparing Two Population Variances and Finding Critical F-Values
• Example A8.2: Constructing a Confidence Interval for the Ratio of Two Population Variances
• Example A8.3: Constructing a Confidence Interval for the Ratio of Two Population Standard Deviations

A.9 Direct Mail

A.10 Type II Errors

A.11 Hypothesis Testing - Two Population Variances

• Examples
• Example A11.1: Performing a Hypothesis Test for Two Population Variances (Left-Tailed)
• Example A11.3: Performing a Hypothesis Test for Two Population Variances (Two-Tailed)

A.12 Estimating Population Variance

• Examples
• Example A12.1: Finding Point Estimates for the Population Standard Deviation and Variance
• Example A12.2: Constructing a Confidence Interval for a Population Variance
• Example A12.3: Constructing a Confidence Interval for a Population Standard Deviation
• Example A12.4: Constructing a Confidence Interval for a Population Variance
• Example A12.5: Constructing a Confidence Interval for a Population Standard Deviation
• Example A12.6: Finding the Minimum Sample Size Needed for a Confidence Interval for a Population Standard Deviation

A.13 c-Charts

• Examples
• Example A13.1: c-Charts

A.14 Mean Charts Using s

• Examples
• Example A14.1: Mean Charts Using s