Chapter 4 discrete random Variables 212 4.1 Two Types of Random Variables 214 4.2 Probability Distributions for Discrete Random Variables 217 4.3 Expected Values of Discrete Random Variables 224 4.4 The Binomial Random Variable 229 4.5 The Poisson Random Variable (Optional) 242 4.6 The Hypergeometric Random Variable (Optional) 247 Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold? 213 Using Technology: MINITAB: Discrete Probabilities 257 TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables and Probabilities 257 Chapter 5 Continuous random Variables 260 5.1 Continuous Probability Distributions 262 5.2 The Uniform Distribution 263 5.3 The Normal Distribution 267 5.4 Descriptive Methods for Assessing Normality 281 5.5 Approximating a Binomial Distribution with a Normal Distribution (Optional) 290 5.6 The Exponential Distribution (Optional) 295 Statistics in Action: Super Weapons Development—Is the Hit Ratio Optimized? 261 Using Technology: MINITAB: Continuous Random Variable Probabilities and Normal Probability Plots 307 TI-83/TI-84 Plus Graphing Calculator: Normal Random Variable and Normal Probability Plots 308 Chapter 6 Sampling distributions 310 6.1 The Concept of a Sampling Distribution 312 6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance 319 6.3 The Sampling Distribution of xQ and the Central Limit Theorem 323 6.4 The Sampling Distribution of the Sample Proportion 332 Statistics in Action: The Insomnia Pill: Is It Effective? 311 Using Technology: MINITAB: Simulating a Sampling Distribution 341 CONTENTS 9 inferences Based on a Single Sample: Chapter 7 estimation with Confidence intervals 342
