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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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