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Chapter 1: Introduction and Graphical Displays 		3
Introduction 		3
Section 1-2 Frequency Distributions 		17
Section 1-3: Dot Plots 		29
Section 1-4: Bar Charts and Bar Graphs 		30
Section 1-5: Histograms 		34
Section 1-6: Frequency and Relative Frequency Polygons 		39
Section 1-7: Ogives 		43
Section 1-8: Stem-and-Leaf Plots or Displays 		50
Section 1-9: Time Series Graphs 		54
Section 1-10: Pie Graphs or Pie Charts 		58
Section 1-11: Pareto Charts 		61
Chapter Review 		63
Chapter 2: Measures of Central Tendency 		64
Introduction 		64
Section 2-2: The Mean 		65
Section 2-3: The Median 		73
Section 2-4: The Mode 		79
Section 2-5: Shapes of Distributions 		91
Chapter Review 		96
Chapter 3: Measures of Variability 		97
Introduction 		97
Section 3-2: The Range 		98
Section 3-3: The Interquartile Range 		103
Section 3-4: The Mean Absolute Deviation 		108
Section 3-5: The Variance and Standard Deviation 		114
Section 3-6: The Coefficient of Variation 		122
Section 3-7: The Empirical Rule 		127
Section 3-8: Measuring Skewness 		139
Chapter Review 		145
Chapter 4: Measures of Position 		146
Introduction 		146
Section 4-2: The z-Score or Standard Score 		147
Section 4-3: Percentile 		154
Section 4-4: Outliers 		165
Section 4-5: Box Plots 		170
Chapter Review 		180
Chapter 5: Bivariate Data 		181
Introduction 		181
Section 5-2: Scatter Plots 		181
Section 5-3: Looking for Patterns in the Data 		184
Section 5-4: Linear Correlation 		192
Section 5-5: Correlation and Causation 		202
Section 5-6: Regression Analysis and the Least Squares Regression Line 		204
Section 5-7: The Coefficient of Determination 		215
Section 5-8: Residual Plots 		217
Section 5-9: Outliers and Influential Points 		230
Chapter Review 		236
Chapter 6: Categorical Data 		237
Introduction 		237
Section 6-2: Joint and Marginal Distributions 		238
Section 6-3: Conditional Distributions 		244
Section 6-4: Independence in Categorical Variables 		252
Section 6-5: Simpson's Paradox 		257
Chapter Review 		265
Chapter 7: Probability 		266
Introduction 		266
Section 7-2: Randomness and Uncertainty 		267
Section 7-3: Random Experiments, Sample Space and Events 		268
Section 7-4: Classical Probability 		272
Section 7-5: Relative Frequency or Empirical Probability 		275
Section 7-6: The Law of Large Numbers 		277
Section 7-7: Subjective Probability 		281
Section 7-8: Some Basic Rules of Probability 		282
Section 7-9: Others Rules of Probability 		283
Section 7-10: Conditional Probability 		296
Section 7-11: Independence 		299
Chapter Review 		303
Chapter 8: Discrete Probability Distributions 		304
Introduction 		304
Section 8-2: Random Variables 		305
Section 8-3: Probability Distributions for Discrete Random Variables 		310
Section 8-4: Expected Value for a Discrete Random Variable 		313
Section 8-5: Variance and Standard Deviation of a Discrete Random Variable 		320
Section 8-6: Bernoulli Trials and the Binomial Probability Distribution 		328
Section 8-7: The Geometric Probability Distribution 		336
Section 8-8: The Poisson Probability Distribution 		342
Section 8-9: The Hypergeometric Probability Distribution 		347
Chapter Review 		356
Chapter 9: The Normal Probability Distribution 		357
Introduction 		357
Section 9-2: The Normal Probability Distribution 		359
Section 9-3: Properties of the Normal Distribution 		363
Section 9-4: The Standard Normal Distribution 		374
Section 9-5: Applications of the Normal Distribution 		394
Section 9-6: The Normal Approximation to the Binomial Distribution 		400
Chapter Review 		414
Chapter 10: Sampling Distributions and the Central Limit Theorem 		415
Introduction 		415
Section 10-2: Sampling Distribution of a Sample Proportion 		415
Section 10-3: Sampling Distribution of a Sample Mean 		428
Section 10-4 Sampling Distribution for the Difference Between two Independent Sample Proportions 		440
Section 10-5 Sampling Distribution for the Difference Between two Independent Sample Means 		453
Chapter Review 		466
Chapter 11: Confidence Intervals - Large Samples 		467
Introduction 		467
Section 11-2: Large Sample Confidence Interval for a Single Population Proportion 		468
Section 11-3: Large Sample Confidence Interval for a Single Population Mean 		481
Section 11-4: Large Sample Confidence Interval for the Difference Between Two Population Proportions 		491
Section 11-5: Large Sample Confidence Interval for the Difference Between Two Population Means 		499
Chapter Review 		511
Chapter 12: Hypothesis Tests - Large Samples 		512
Introduction 		512
Section 12-2: Some Terms Associated with Hypothesis Testing 		513
Section 12-3: Large Sample Test for a Single Population Proportion 		520
Section 12-4 Large Sample Tests for a Single Population Mean 		533
Section 12-5: Large Sample Test for the Difference Between Two Population Proportions 		546
Section 12-6: Large Sample Tests for the Difference Between Two Population Means 		562
Chapter Review 		581
Chapter 13: Confidence Intervals - Small Samples 		582
Introduction 		582
Section 13-2: The t-Distribution 		583
Section 13-3: Small Sample Confidence Interval for a Single Population Mean 		587
Section 13-4: Small Sample Confidence Interval for the Difference Between Two Population Means Using Independent Samples 		592
Section 13-5: Small Sample Confidence Interval for the Difference Between Two Population Means Using Dependent Samples 		602
Chapter Review 		611
Chapter 14: Hypothesis Tests - Small Samples 		612
Introduction 		612
Section 14-2 Small Sample Test for a Single Population Mean 		612
Section 14-3: Small Sample Hypothesis Tests for the Difference Between Two Population Means Using Independent Samples 		628
Section 14-4: Small Sample Hypothesis Tests for the Difference Between Two Population Means Using Dependent Samples 		652
Chapter Review 		659
Chapter 15: Chi-Square Tests 		660
Introduction 		660
Section 15-2: The Chi-Square Distribution 		661
Section 15-3: The Chi-Square Test for Goodness-of-Fit 		666
Section 15-4: The Chi-Square Test for Independence 		686
Section 15-5: Benford's Law 		693
Chapter Review 		706
Chapter 16: One-Way Analysis of Variance 		707
Introduction 		707
Section 16-2: Comparing Population Means Graphically 		708
Section 16-3: Terminology Associated with Analysis of Variance (ANOVA) 		716
Section 16-4 The Hypotheses and Assumptions for One-Way ANOVA 		721
Section 16-5: The F-Distribution and the F Test Statistic 		729
Section 16-6: One-Way or Single Factor ANOVA Test for the Equality of Several Population Means 		733
Section 16-7: The One-Way ANOVA Model and Validating the Model Assumptions 		742
Chapter Review 		754
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