What Is Statistics? p. 1 Introduction p. 2 Why Study Statistics? p. 2 What Is Meant by Statistics? p. 4 Types of Statistics p.

Transcription

1 What Is Statistics? p. 1 Introduction p. 2 Why Study Statistics? p. 2 What Is Meant by Statistics? p. 4 Types of Statistics p. 6 Descriptive Statistics p. 6 Inferential Statistics p. 7 Types of Variables p. 9 Levels of Measurement p. 9 Nominal-Level Data p. 10 Ordinal-Level Data p. 11 Interval-Level Data p. 12 Ratio-Level Data p. 12 Exercises p. 14 Statistics, Graphics, and Ethics p. 15 Misleading Statistics p. 15 Association Does Not Necessarily Imply Causation p. 15 Graphs Can Be Misleading p. 16 Become a Better Consumer and a Better Producer of Information p. 17 Ethics p. 17 Software Applications p. 18 Chapter Outline p. 19 Chapter Exercises p. 19 exercises.com p. 20 Dataset Exercises p. 21 Answers to Self-Review p. 22 Describing Data: Frequency Distributions and Graphic Presentation p. 23 Introduction p. 24 Constructing a Frequency Distribution p. 25 Class Intervals and Class Midpoints p. 29 A Software Example p. 29 Relative Frequency Distribution p. 30 Exercises p. 31 Graphic Presentation of a Frequency Distribution p. 32 Histogram p. 32 Frequency Polygon p. 34 Exercises p. 37 Cumulative Frequency Distributions p. 38 Exercises p. 41 Other Graphic Presentations of Data p. 42 Line Graphs p. 42

2 Bar Charts p. 43 Pie Charts p. 44 Exercises p. 46 Chapter Outline p. 47 Chapter Exercises p. 48 exercises.com p. 53 Dataset Exercises p. 53 Software Commands p. 54 Answers to Self-Review p. 56 Describing Data: Numerical Measures p. 57 Introduction p. 58 The Population Mean p. 59 The Sample Mean p. 60 Properties of the Arithmetic Mean p. 61 Exercises p. 62 The Weighted Mean p. 63 Exercises p. 64 The Median p. 64 The Mode p. 65 Exercises p. 67 Software Solution p. 68 The Relative Positions of the Mean, Median, and Mode p. 68 Exercises p. 70 The Geometric Mean p. 71 Exercises p. 72 Why Study Dispersion? p. 73 Measures of Dispersion p. 74 Range p. 74 Mean Deviation p. 75 Exercises p. 76 Variance and Standard Deviation p. 77 Exercises p. 79 Software Solution p. 80 Exercises p. 81 Interpretation and Uses of the Standard Deviation p. 82 Chebyshev's Theorem p. 82 The Empirical Rule p. 83 Exercises p. 84 Chapter Outline p. 84 Pronunciation Key p. 86 Chapter Exercises p. 86

3 exercises.com p. 89 Dataset Exercises p. 90 Software Commands p. 90 Answers to Self-Review p. 92 Describing Data: Displaying and Exploring Data p. 93 Introduction p. 94 Dot Plots p. 94 Exercises p. 96 Quartiles, Deciles, and Percentiles p. 97 Exercises p. 100 Box Plots p. 100 Exercises p. 102 Skewness p. 103 Exercises p. 107 Describing the Relationship between Two Variables p. 107 Exercises p. 110 Chapter Outline p. 112 Pronunciation Key p. 112 Chapter Exercises p. 112 exercises.com p. 116 Dataset Exercises p. 116 Software Commands p. 117 Answers to Self-Review p. 119 A Survey of Probability Concepts p. 120 Introduction p. 121 What Is a Probability? p. 122 Approaches to Assigning Probabilities p. 124 Classical Probability p. 124 Empirical Probability p. 125 Subjective Probability p. 126 Exercises p. 127 Some Rules for Computing Probabilities p. 128 Rules of Addition p. 128 Exercises p. 133 Rules of Multiplication p. 134 Contingency Tables p. 137 Tree Diagrams p. 139 Exercises p. 141 Principles of Counting p. 142 The Multiplication Formula p. 142 The Permutation Formula p. 143

4 The Combination Formula p. 145 Exercises p. 146 Chapter Outline p. 147 Pronunciation Key p. 148 Chapter Exercises p. 148 exercises.com p. 152 Dataset Exercises p. 152 Software Commands p. 153 Answers to Self-Review p. 154 Discrete Probability Distributions p. 156 Introduction p. 157 What Is a Probability Distribution? p. 157 Random Variables p. 159 Discrete Random Variable p. 159 Continuous Random Variable p. 160 The Mean, Variance, and Standard Deviation of a Probability Distribution p. 160 Mean p. 160 Variance and Standard Distribution p. 161 Exercises p. 163 Binomial Probability Distribution p. 164 How Is a Binomial Probability Distribution Computed p. 165 Binomial Probability Tables p. 167 Exercises p. 170 Cumulative Binomial Probability Distributions p. 172 Exercises p. 173 Poisson Probability Distribution p. 174 Exercises p. 177 Chapter Outline p. 177 Chapter Exercises p. 178 Dataset Exercises p. 182 Software Commands p. 182 Answers to Self-Review p. 184 Continuous Probability Distributions p. 185 Introduction p. 186 The Family of Uniform Distributions p. 186 Exercises p. 189 The Family of Normal Probability Distributions p. 190 The Standard Normal Distribution p. 193 The Empirical Rule p. 195 Exercises p. 196 Finding Areas under the Normal Curve p. 197

5 Exercises p. 199 Exercises p. 202 Exercises p. 204 Chapter Outline p. 204 Chapter Exercises p. 205 Dataset Exercises p. 208 Software Commands p. 209 Answers to Self-Review p. 210 Sampling Methods and the Central Limit Theorem p. 211 Introduction p. 212 Sampling Methods p. 212 Reasons to Sample p. 212 Simple Random Sampling p. 213 Systematic Random Sampling p. 216 Stratified Random Sampling p. 216 Cluster Sampling p. 217 Exercises p. 218 Sampling "Error" p. 220 Sampling Distribution of the Sample Mean p. 222 Exercises p. 225 The Central Limit Theorem p. 226 Exercises p. 232 Using the Sampling Distribution of the Sample Mean p. 233 Exercises p. 237 Chapter Outline p. 237 Pronunciation Key p. 238 Chapter Exercises p. 238 exercises.com p. 242 Dataset Exercises p. 243 Software Commands p. 243 Answers to Self-Review p. 244 Estimation and Confidence Intervals p. 245 Introduction p. 246 Point Estimates and Confidence Intervals p. 246 Known [sigma] or a Large Sample p. 246 A Computer Simulation p. 251 Exercises p. 253 Unknown Population Standard Deviation and a Small Sample p. 254 Exercises p. 260 A Confidence Interval for a Proportion p. 260 Exercises p. 263

6 Finite-Population Correction Factor p. 263 Exercises p. 264 Choosing an Appropriate Sample Size p. 265 Exercises p. 267 Chapter Outline p. 268 Pronunciation Key p. 269 Chapter Exercises p. 269 exercises.com p. 272 Dataset Exercises p. 273 Software Commands p. 273 Answers to Self-Review p. 275 One-Sample Tests of Hypothesis p. 276 Introduction p. 277 What Is a Hypothesis? p. 277 What Is Hypothesis Testing? p. 278 Five-Step Procedure for Testing a Hypothesis p. 278 State the Null Hypothesis (H[subscript 0]) and the Alternate Hypothesis (H[subscript 1]) p. 278 Select a Level of Significance p. 279 Select the Test Statistic p. 279 Formulate the Decision Rule p. 281 Make a Decision p. 282 One-Tailed and Two-Tailed Tests of Significance p. 283 Testing for a Population Mean with a Known Population Standard Deviation p. 284 A Two-Tailed Test p. 284 A One-Tailed Test p. 288 p-value in Hypothesis Testing p. 288 Testing for a Population Mean: Large Sample, Population Standard Deviation Unknown p. 290 Exercises p. 291 Tests Concerning Proportions p. 292 Exercises p. 295 Testing for a Population Mean: Small Sample, Population Standard Deviation Unknown p. 295 Exercises p. 300 A Software Solution p. 301 Exercises p. 303 Chapter Outline p. 304 Pronunciation Key p. 305 Chapter Exercises p. 305 exercises.com p. 309 Dataset Exercises p. 309

7 Software Commands p. 310 Answers to Self-Review p. 311 Two-Sample Tests of Hypothesis p. 312 Introduction p. 313 Two-Sample Tests of Hypothesis: Independent Samples p. 313 Exercises p. 318 Two-Sample Tests about Proportions p. 319 Exercises p. 321 Comparing Population Means with Small Samples p. 323 Exercises p. 326 Two-Sample Tests of Hypothesis: Dependent Samples p. 327 Comparing Dependent and Independent Samples p. 331 Exercises p. 333 Chapter Outline p. 334 Pronunciation Key p. 335 Chapter Exercises p. 335 exercises.com p. 340 Dataset Exercises p. 341 Software Commands p. 341 Answers to Self-Review p. 342 Analysis of Variance p. 344 Introduction p. 345 The F Distribution p. 345 Comparing Two Population Variances p. 346 Exercises p. 349 ANOVA Assumptions p. 350 The ANOVA Test p. 352 Exercises p. 359 Inferences about Pairs of Treatment Means p. 360 Exercises p. 362 Chapter Outline p. 364 Pronunciation Key p. 365 Chapter Exercises p. 365 exercises.com p. 370 Dataset Exercises p. 370 Software Commands p. 371 Answers to Self-Review p. 373 Linear Regression and Correlation p. 374 Introduction p. 375 What Is Correlation Analysis? p. 375 The Coefficient of Correlation p. 377

8 The Coefficient of Determination p. 381 Correlation and Cause p. 382 Exercises p. 382 Testing the Significance of the Correlation Coefficient p. 384 Exercises p. 386 Regression Analysis p. 386 Least Squares Principle p. 386 Drawing the Line of Regression p. 389 Exercises p. 390 The Standard Error of Estimate p. 392 Assumptions Underlying Linear Regression p. 395 Exercises p. 396 Confidence and Prediction Intervals p. 396 Exercises p. 400 More on the Coefficient of Determination p. 400 Exercises p. 403 The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimate p. 403 Transforming Data p. 405 Exercises p. 407 Chapter Outline p. 408 Pronunciation Key p. 410 Chapter Exercises p. 410 exercises.com p. 417 Dataset Exercises p. 417 Software Commands p. 418 Answers to Self-Review p. 420 Multiple Regression and Correlation Analysis p. 421 Introduction p. 422 Multiple Regression Analysis p. 422 Inferences in Multiple Linear Regression p. 423 Exercises p. 426 Multiple Standard Error of Estimate p. 428 Assumptions about Multiple Regression and Correlation p. 429 The ANOVA Table p. 430 Exercises p. 432 Evaluating the Regression Equation p. 432 Using a Scatter Diagram p. 432 Correlation Matrix p. 433 Global Test: Testing the Multiple Regression Model p. 434 Evaluating Individual Regression Coefficients p. 436 Qualitative Independent Variables p. 439

9 Exercises p. 441 Analysis of Residuals p. 442 Chapter Outline p. 447 Pronunciation Key p. 448 Chapter Exercises p. 448 exercises.com p. 459 Dataset Exercises p. 460 Software Commands p. 461 Answers to Self-Review p. 463 Chi-Square Applications p. 464 Introduction p. 464 Goodness-of-Fit Test: Equal Expected Frequencies p. 465 Exercises p. 470 Goodness-of-Fit Test: Unequal Expected Frequencies p. 471 Limitations of Chi-Square p. 473 Exercises p. 475 Contingency Table Analysis p. 746 Exercises p. 450 Chapter Outline p. 481 Pronunciation Key p. 481 Chapter Exercises p. 482 exercises.com p. 484 Dataset Exercises p. 485 Software Commands p. 486 Answers to Self-Review p. 487 CD Chapters Statistical Quality Control Time Series and Forecasting Appendixes Tables Binomial Probability Distribution p. 489 Critical Values of Chi-Square p. 494 Poisson Distribution p. 495 Areas under the Normal Curve p. 496 Table of Random Numbers p. 497 Student's t Distribution p. 498 Critical Values of the F Distribution p. 499 Wilcoxon T Values p. 501 Factors for Control Charts p. 502 Datasets Real Estate p. 503

10 Major League Baseball p. 506 Wages and Wage Earners p. 508 CIA International Economic and Demographic Data p. 512 Whitner Autoplex p. 515 Getting Started with Megastat p. 516 Visual Statistics p. 520 Answers to Odd-Numbered Exercises p. 525 Photo Credits p. 552 Index p. 553 Table of Contents provided by Blackwell's Book Services and R.R. Bowker. Used with permission.