1. CHAPTER 1 Introduction
2. 1.1 Statistics and Types of Statistics
3. Case Study 1–1 2014 Lobbying Spending by Selected Companies
4. Case Study 1–2 Americans Life Outlook, 2014
5. 1.2 Basic Terms
6. 1.3 Types of Variables
7. 1.4 Cross-Section Versus Time-Series Data
8. 1.5 Population Versus Sample
9. 1.6 Design of Experiments
10. 1.7 Summation Notation
11. Uses and Misuses
12. Glossary
13. Supplementary Exercises
14. Advanced Exercises
15. Self-Review Test
16. Technology Instructions
17. Technology Assignments
18. CHAPTER 2 Organizing and Graphing Data
19. 2.1 Organizing and Graphing Qualitative Data
20. Case Study 2–1 Ideological Composition of the U.S. Public, 2014
21. Case Study 2–2 Millennials’ Views on Their Level of Day-to-Day Banking Knowledge
22. 2.2 Organizing and Graphing Quantitative Data
23. Case Study 2–3 Car Insurance Premiums per Year in 50 States
24. Case Study 2–4 Hours Worked in a Typical Week by Full-Time U.S. Workers
25. Case Study 2–5 How Many Cups of Coffee Do You Drink a Day?
26. 2.3 Stem-and-Leaf Displays
27. 2.4 Dotplots
28. Uses and Misuses
29. Glossary
30. Supplementary Exercises
31. Advanced Exercises
32. Self-Review Test
33. Technology Instructions
34. Technology Assignments
35. CHAPTER 3 Numerical Descriptive Measures
36. 3.1 Measures of Center for Ungrouped Data
37. Case Study 3–1 2013 Average Starting Salaries for Selected Majors
38. Case Study 3–2 Education Level and 2014 Median Weekly Earnings
39. 3.2 Measures of Dispersion for Ungrouped Data
40. 3.3 Mean, Variance, and Standard Deviation for Grouped Data
41. 3.4 Use of Standard Deviation
42. Case Study 3–3 Does Spread Mean the Same as Variability and Dispersion?
43. 3.5 Measures of Position
44. 3.6 Box-and-Whisker Plot
45. Uses and Misuses
46. Glossary
47. Supplementary Exercises
48. Advanced Exercises
49. Appendix 3.1
50. Self-Review Test
51. Technology Instructions
52. Technology Assignments
53. CHAPTER 4 Probability
54. 4.1 Experiment, Outcome, and Sample Space
55. 4.2 Calculating Probability
56. 4.3 Marginal Probability, Conditional Probability, and Related Probability Concepts
57. Case Study 4–1 Do You Worry About Your Weight?
58. 4.4 Intersection of Events and the Multiplication Rule
59. 4.5 Union of Events and the Addition Rule
60. 4.6 Counting Rule, Factorials, Combinations, and Permutations
61. Case Study 4–2 Probability of Winning a Mega Millions Lottery Jackpot
62. Uses and Misuses
63. Glossary
64. Supplementary Exercises
65. Advanced Exercises
66. Self-Review Test
67. Technology Instructions
68. Technology Assignments
69. CHAPTER 5 Discrete Random Variables and Their Probability Distributions
70. 5.1 Random Variables
71. 5.2 Probability Distribution of a Discrete Random Variable
72. 5.3 Mean and Standard Deviation of a Discrete Random Variable
73. Case Study 5–1 All State Lottery
74. 5.4 The Binomial Probability Distribution
75. 5.5 The Hypergeometric Probability Distribution
76. 5.6 The Poisson Probability Distribution
77. Case Study 5–2 Global Birth and Death Rates
78. Uses and Misuses
79. Glossary
80. Supplementary Exercises
81. Advanced Exercises
82. Self-Review Test
83. Technology Instructions
84. Technology Assignments
85. CHAPTER 6 Continuous Random Variables and the Normal Distribution
86. 6.1 Continuous Probability Distribution and the Normal Probability Distribution
87. Case Study 6–1 Distribution of Time Taken to Run a Road Race
88. 6.2 Standardizing a Normal Distribution
89. 6.3 Applications of the Normal Distribution
90. 6.4 Determining the z and x Values When an Area Under the Normal Distribution Curve Is Known
91. 6.5 The Normal Approximation to the Binomial Distribution
92. Uses and Misuses
93. Glossary
94. Supplementary Exercises
95. Advanced Exercises
96. Appendix 6.1
97. Self-Review Test
98. Technology Instructions
99. Technology Assignments
100. CHAPTER 7 Sampling Distributions
101. 7.1 Sampling Distribution, Sampling Error, and Nonsampling Errors
102. 7.2 Mean and Standard Deviation of x
103. 7.3 Shape of the Sampling Distribution of x
104. 7.4 Applications of the Sampling Distribution of x
105. 7.5 Population and Sample Proportions; and the Mean, Standard Deviation, and Shape of the Sampling D
106. 7.6 Applications of the Sampling Distribution of p
107. Uses and Misuses
108. Glossary
109. Supplementary Exercises
110. Advanced Exercises
111. Self-Review Test
112. Technology Instructions
113. Technology Assignments
114. CHAPTER 8 Estimation of the Mean and Proportion
115. 8.1 Estimation, Point Estimate, and Interval Estimate
116. 8.2 Estimation of a Population Mean: σ Known
117. Case Study 8–1 Annual Salaries of Registered Nurses, 2014
118. 8.3 Estimation of a Population Mean: σ Not Known
119. 8.4 Estimation of a Population Proportion: Large Samples
120. Case Study 8–2 Americans’ Efforts to Lose Weight Still Trail Desires
121. Uses and Misuses
122. Glossary
123. Supplementary Exercises
124. Advanced Exercises
125. Self-Review Test
126. Technology Instructions
127. Technology Assignments
128. CHAPTER 9 Hypothesis Tests About the Mean and Proportion
129. 9.1 Hypothesis Tests: An Introduction
130. 9.2 Hypothesis Tests About µ: σ Known
131. Case Study 9–1 Average Student Loan Debt for the Class of 2013
132. 9.3 Hypothesis Tests About µ: σ Not Known
133. 9.4 Hypothesis Tests About a Population Proportion: Large Samples
134. Case Study 9–2 Are Upper-Income People Paying Their Fair Share in Federal Taxes?
135. Uses and Misuses
136. Glossary
137. Supplementary Exercises
138. Advanced Exercises
139. Self-Review Test
140. Technology Instructions
141. Technology Assignments
142. CHAPTER 10 Estimation and Hypothesis Testing: Two Populations
143. 10.1 Inferences About the Difference Between Two Population Means for Independent Samples: σ1 and
144. 10.2 Inferences About the Difference Between Two Population Means for Independent Samples: σ1 and
145. 10.3 Inferences About the Difference Between Two Population Means for Independent Samples: σ1 and
146. 10.4 Inferences About the Mean of Paired Samples (Dependent Samples)
147. 10.5 Inferences About the Difference Between Two Population Proportions for Large and Independent Sa
148. Uses and Misuses
149. Glossary
150. Supplementary Exercises
151. Advanced Exercises
152. Self-Review Test
153. Technology Instructions
154. Technology Assignments
155. CHAPTER 11 Chi-Square Tests
156. 11.1 The Chi-Square Distribution
157. 11.2 A Goodness-of-Fit Test
158. Case Study 11–1 Are People on Wall Street Honest and Moral?
159. 11.3 A Test of Independence or Homogeneity
160. 11.4 Inferences About the Population Variance
161. Uses and Misuses
162. Glossary
163. Supplementary Exercises
164. Advanced Exercises
165. Self-Review Test
166. Technology Instructions
167. Technology Assignments
168. CHAPTER 12 Analysis of Variance
169. 12.1 The F Distribution
170. 12.2 One-Way Analysis of Variance
171. Uses and Misuses
172. Glossary
173. Supplementary Exercises
174. Advanced Exercises
175. Self-Review Test
176. Technology Instructions
177. Technology Assignments
178. CHAPTER 13 Simple Linear Regression
179. 13.1 Simple Linear Regression
180. Case Study 13–1 Regression of Weights on Heights for NFL Players
181. 13.2 Standard Deviation of Errors and Coefficient of Determination
182. 13.3 Inferences About B
183. 13.4 Linear Correlation
184. 13.5 Regression Analysis: A Complete Example
185. 13.6 Using the Regression Model
186. Uses and Misuses
187. Glossary
188. Supplementary Exercises
189. Advanced Exercises
190. Self-Review Test
191. Technology Instructions
192. Technology Assignments
193. APPENDIX A Explanation of Data Sets
194. APPENDIX B Statistical Tables
195. ANSWERS TO SELECTED ODD-NUMBERED EXERCISES AND SELF-REVIEW TESTS
196. INDEX
197. Key Formulas
198. Standard Normal Distribution Table
199. The t Distribution Table
200. EULA

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