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Contents Chapter 1 What Is Statistics? 1 Introduction 2 Why Study Statistics? 2 What Is Meant by Statistics? 4 Types of Statistics 6 Descriptive Statistics 6 Inferential Statistics 7 Types of Variables 9 Levels of Measurement 9 Nominal-Level Data 10 Ordinal-Level Data 11 Interval-Level Data 12 Ratio-Level Data 12 Exercises 14 Statistics, Graphics, and Ethics 15 Misleading Statistics 15 Association Does Not Necessarily Imply Causation 15 Graphs Can Be Misleading 16 Become a Better Consumer and a Better Producer of Information 17 Ethics 17 Software Applications 18 Chapter Outline 19 Chapter Exercises 19 exercises.com 20 Dataset Exercises 21 Answers to Self-Review 22 Chapter 2 Describing Data: Frequency Distributions and Graphic Presentation 23 Introduction 24 Constructing a Frequency Distribution 25 Class Intervals and Class Midpoints 29 A Software Example 29 Relative Frequency Distribution 30 Exercises 31 Graphic Presentation of a Frequency Distribution 32 Histogram 32 Frequency Polygon 34 Exercises 37 Cumulative Frequency Distributions 38 Exercises 41 Other Graphic Presentations of Data 42 Line Graphs 42 Bar Charts 43 Pie Charts 44 Exercises 46 Chapter Outline 47 Chapter Exercises 48 exercises.com 53 Dataset Exercises 53 Software Commands 54 Answers to Self-Review 56 Chapter 3 Describing Data: Numerical Measures 57 Introduction 58 The Population Mean 59 The Sample Mean 60 Properties of the Arithmetic Mean 61 Exercises 62 The Weighted Mean 63 Exercises 64 The Median 64 The Mode 65 Exercises 67 Software Solution 68 The Relative Positions of the Mean, Median, and Mode 68 Exercises 70 The Geometric Mean 71 Exercises 72 Why Study Dispersion? 73 Measures of Dispersion 74 Range 74 Mean Deviation 75 Exercises 76 Variance and Standard Deviation 77 Exercises 79 Software Solution 80 Exercises 81 Interpretation and Uses of the Standard Deviation 82 Chebyshev?s Theorem 82 The Empirical Rule 83 Exercises 84 Chapter Outline 84 Pronunciation Key 86 Chapter Exercises 86 exercises.com 89 Dataset Exercises 90 Software Commands 90 Answers to Self-Review 92 Chapter 4 Describing Data: Displaying and Exploring Data 93 Introduction 94 Dot Plots 94 Exercises 96 Quartiles, Deciles, and Percentiles 97 Exercises 100 Box Plots 100 Exercises 102 Skewness 103 Exercises 107 Describing the Relationship between Two Variables 107 Exercises 110 Chapter Outline 112 Pronunciation Key 112 Chapter Exercises 112 exercises.com 116 Dataset Exercises 116 Software Commands 117 Answers to Self-Review 119 Chapter 5 A Survey of Probability Concepts 120 Introduction 121 What Is a Probability? 122 Approaches to Assigning Probabilities 124 Classical Probability 124 Empirical Probability 125 Subjective Probability 126 Exercises 127 Some Rules for Computing Probabilities 128 Rules of Addition 128 Exercises 133 Rules of Multiplication 134 Contingency Tables 137 Tree Diagrams 139 Exercises 141 Principles of Counting 142 The Multiplication Formula 142 The Permutation Formula 143 The Combination Formula 145 Exercises 146 Chapter Outline 147 Pronunciation Key 148 Chapter Exercises 148 exercises.com 152 Dataset Exercises 152 Software Commands 153 Answers to Self-Review 154 Chapter 6 Discrete Probability Distributions 156 Introduction 157 What Is a Probability Distribution? 157 Random Variables 159 Discrete Random Variable 159 Continuous Random Variable 160 The Mean, Variance, and Standard Deviation of a Probability Distribution 160 Mean 160 Variance and Standard Distribution 161 Exercises 163 Binomial Probability Distribution 164 How Is a Binomial Probability Distribution Computed 165 Binomial Probability Tables 167 Exercises 170 Cumulative Binomial Probability Distributions 172 Exercises 173 Poisson Probability Distribution 174 Exercises 177 Chapter Outline 177 Chapter Exercises 178 Dataset Exercises 182 Software Commands 182 Answers to Self-Review 184 Chapter 7 Continuous Probability Distributions 185 Introduction 186 The Family of Uniform Distributions 186 Exercises 189 The Family of Normal Probability Distributions 190 The Standard Normal Distribution 193 The Empirical Rule 195 Exercises 196 Finding Areas under the Normal Curve 197 Exercises 199 Exercises 202 Exercises 204 Chapter Outline 204 Chapter Exercises 205 Dataset Exercises 208 Software Commands 209 Answers to Self-Review 210 Chapter 8 Sampling Methods and the Central Limit Theorem 211 Introduction 212 Sampling Methods 212 Reasons to Sample 212 Simple Random Sampling 213 Systematic Random Sampling 216 Stratified Random Sampling 216 Cluster Sampling 217 Exercises 218 Sampling ?Error? 220 Sampling Distribution of the Sample Mean 222 Exercises 225 The Central Limit Theorem 226 Exercises 232 Using the Sampling Distribution of the Sample Mean 233 Exercises 237 Chapter Outline 237 Pronunciation Key 238 Chapter Exercises 238 exercises.com 242 Dataset Exercises 243 Software Commands 243 Answers to Self-Review 244 Chapter 9 Estimation and Confidence Intervals 245 Introduction 246 Point Estimates and Confidence Intervals 246 Known _ or a Large Sample 246 A Computer Simulation 251 Exercises 253 Unknown Population Standard Deviation and a Small Sample 254 Exercises 260 A Confidence Interval for a Proportion 260 Exercises 263 Finite-Population Correction Factor 263 Exercises 264 Choosing an Appropriate Sample Size 265 Exercises 267 Chapter Outline 268 Pronunciation Key 269 Chapter Exercises 269 exercises.com 272 Dataset Exercises 273 Software Commands 273 Answers to Self-Review 275 Chapter 10 One-Sample Tests of Hypothesis 276 Introduction 277 What Is a Hypothesis? 277 What Is Hypothesis Testing? 278 Five-Step Procedure for Testing a Hypothesis 278 Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1) 278 Step 2: Select a Level of Significance 279 Step 3: Select the Test Statistic 279 Step 4: Formulate the Decision Rule 281 Step 5: Make a Decision 282 One-Tailed and Two-Tailed Tests of Significance 283 Testing for a Population Mean with a Known Population Standard Deviation 284 A Two-Tailed Test 284 A One-Tailed Test 288 p-Value in Hypothesis Testing 288 Testing for a Population Mean: Large Sample, Population Standard Deviation Unknown 290 Exercises 291 Tests Concerning Proportions 292 Exercises 295 Testing for a Population Mean: Small Sample, Population Standard Deviation Unknown 295 Exercises 300 A Software Solution 301 Exercises 303 Chapter Outline 304 Pronunciation Key 305 Chapter Exercises 305 exercises.com 309 Dataset Exercises 309 Software Commands 310 Answers to Self-Review 311 Chapter 11 Two-Sample Tests of Hypothesis 312 Introduction 313 Two-Sample Tests of Hypothesis: Independent Samples 313 Exercises 318 Two-Sample Tests about Proportions 319 Exercises 321 Comparing Population Means with Small Samples 323 Exercises 326 Two-Sample Tests of Hypothesis: Dependent Samples 327 Comparing Dependent and Independent Samples 331 Exercises 333 Chapter Outline 334 Pronunciation Key 335 Chapter Exercises 335 exercises.com 340 Dataset Exercises 341 Software Commands 341 Answers to Self-Review 342 Chapter 12 Analysis of Variance 344 Introduction 345 The F Distribution 345 Comparing Two Population Variances 346 Exercises 349 ANOVA Assumptions 350 The ANOVA Test 352 Exercises 359 Inferences about Pairs of Treatment Means 360 Exercises 362 Chapter Outline 364 Pronunciation Key 365 Chapter Exercises 365 exercises.com 370 Dataset Exercises 370 Software Commands 371 Answers to Self-Review 373 Chapter 13 Linear Regression and Correlation 374 Introduction 375 What Is Correlation Analysis? 375 lin83965_fm.qxd 11/9/04 12:24 PM Page xiv Contents xv The Coefficient of Correlation 377 The Coefficient of Determination 381 Correlation and Cause 382 Exercises 382 Testing the Significance of the Correlation Coefficient 384 Exercises 386 Regression Analysis 386 Least Squares Principle 386 Drawing the Line of Regression 389 Exercises 390 The Standard Error of Estimate 392 Assumptions Underlying Linear Regression 395 Exercises 396 Confidence and Prediction Intervals 396 Exercises 400 More on the Coefficient of Determination 400 Exercises 403 The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimate 403 Transforming Data 405 Exercises 407 Chapter Outline 408 Pronunciation Key 410 Chapter Exercises 410 exercises.com 417 Dataset Exercises 417 Software Commands 418 Answers to Self-Review 420 Chapter 14 Multiple Regression and Correlation Analysis 421 Introduction 422 Multiple Regression Analysis 422 Inferences in Multiple Linear Regression 423 Exercises 426 Multiple Standard Error of Estimate 428 Assumptions about Multiple Regression and Correlation 429 The ANOVA Table 430 Exercises 432 Evaluating the Regression Equation 432 Using a Scatter Diagram 432 Correlation Matrix 433 Global Test: Testing the Multiple Regression Model 434 Evaluating Individual Regression Coefficients 436 Qualitative Independent Variables 439 Exercises 441 Analysis of Residuals 442 Chapter Outline 447 Pronunciation Key 448 Chapter Exercises 448 exercises.com 459 Dataset Exercises 460 Software Commands 461 Answers to Self-Review 463 Chapter 15 Chi-Square Applications 464 Introduction 464 Goodness-of-Fit Test: Equal Expected Frequencies 465 Exercises 470 Goodness-of-Fit Test: Unequal Expected Frequencies 471 Limitations of Chi-Square 473 Exercises 475 Contingency Table Analysis 746 Exercises 450 Chapter Outline 481 Pronunciation Key 481 Chapter Exercises 482 exercises.com 484 Dataset Exercises 485 Software Commands 486 Answers to Self-Review 487 CD Chapters ? Statistical Quality Control ? Time Series and Forecasting Appendixes Appendixes A?I Tables Binomial Probability Distribution 489 Critical Values of Chi-Square 494 Poisson Distribution 495 Areas under the Normal Curve 496 Table of Random Numbers 497 Student?s t Distribution 498 Critical Values of the F Distribution 499 Wilcoxon T Values 501 Factors for Control Charts 502 Appendixes J?N Datasets Real Estate 503 Major League Baseball 506 Wages and Wage Earners 508 CIA International Economic and Demographic Data 512 Whitner Autoplex 515 Appendix O Getting Started with Megastat 516 Appendix P Visual Statistics 520 Answers to Odd-Numbered Exercises 525 Photo Credits 552 Index 553

Library of Congress Subject Headings for this publication:

Social sciences -- Statistical methods.

Economics -- Statistical methods.

Industrial management -- Statistical methods.