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Statistics, Data, and Statistical Thinking | |

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The Science of Statistics | |

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Types of Statistical Applications | |

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Fundamental Elements of Statistics | |

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Types of Data | |

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Collecting Data | |

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The Role of Statistics in Critical Thinking | |

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Methods for Describing Sets of Data | |

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Describing Qualitative Data | |

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Graphical Methods for Describing Quantitative Data | |

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Summation Notation | |

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Numerical Measures of Central Tendency | |

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Numerical Measures of Variability | |

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Interpreting the Standard Deviation | |

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Numerical Measures of Relative Standing | |

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Methods for Detecting Outliers (Optional) | |

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Graphing Bivariate Relationships (Optional) | |

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Distorting the Truth with Descriptive Techniques | |

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Probability | |

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Events, Sample Spaces, and Probability | |

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Unions and Intersections | |

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Complementary Events | |

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The Additive Rule and Mutually Exclusive Events | |

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Conditional Probability | |

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The Multiplicative Rule and Independent Events | |

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Random Sampling | |

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Some Counting Rules (Optional) | |

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Discrete Random Variables | |

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Two Types of Random Variables | |

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Probability Distributions for Discrete Random Variables | |

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Expected Values of Discrete Random Variables | |

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The Binomial Random Variable | |

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The Poisson Random Variable (Optional) | |

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The Hypergeometric Random Variable (Optional) | |

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Continuous Random Variables | |

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Continuous Probability Distributions | |

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The Uniform Distribution | |

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The Normal Distribution | |

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Descriptive Methods for Assessing Normality | |

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Approximating a Binomial Distribution with a Normal Distribution (Optional) | |

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The Exponential Distribution (Optional) | |

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Sampling Distributions | |

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What Is a Sampling Distribution? Properties of Sampling Distributions | |

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Unbiasedness and Minimum Variance (Optional) | |

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The Central Limit Theorem | |

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Inferences Based on a Single Sample: Estimation with Confidence Intervals | |

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Large-Sample Confidence Interval for a Population Mean | |

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Small-Sample Confidence Interval for a Population Mean | |

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Large-Sample Confidence Interval for a Population Proportion | |

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Determining the Sample Size | |

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Inferences Based on a Single Sample: Tests of Hypotheses | |

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The Elements of a Test of Hypothesis | |

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Large-Sample Test of Hypothesis about a Population Mean | |

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Observed Significance Levels: p-Values | |

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Small-Sample Test of Hypothesis about a Population Mean | |

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Large-Sample Test of Hypothesis about a Population Proportion | |

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Calculating Type II Error Probabilities: More about hellip;b (Optional) | |

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Test of Hypothesis about a Population Proportion | |

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Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses | |

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Comparing Two Population Means: Independent Sampling | |

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Comparing Two Population Means: Paired Difference Experiments | |

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Comparing Two Population Proportions: Independent Sampling | |

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Determining the Sample Size | |

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Comparing Two Population Variances: Independent Sampling (Optional) | |

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Analysis of Variance: Comparing More Than Two Means | |

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Elements of a Designed Experiment | |

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The Completely Randomized Design | |

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Multiple Comparisons of Means | |

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The Randomized Block Design | |

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Factorial Experiments | |

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Simple Linear Regression | |

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Probabalistic Models | |

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Fitting the Model: The Least Squares Approach | |

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Model Assumptions | |

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An Estimator of hellip;s2 | |

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Assessing the Utility of the Model: Making Inferences about the Slope hellip;b1 | |

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The Coefficient of Correlation | |

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The Coefficient of Determination | |

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Using the Model for Estimation and Prediction | |

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A Complete Example | |

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Multiple Regression and Model Building | |

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Multiple Regression Models | |

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The First-Order Model: Estimating and Interpreting the hellip;b Parameters | |

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Model Assumptions | |

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Inferences About the Individual hellip;b Parameters | |

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Checking the Overall Utility of a Model | |

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Using the Model for Estimation and Prediction | |

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Model Building: Interaction Models | |

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Model Building: Quadratic and Other Higher-Order Models | |

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Model Building: Qualitative (Dummy) Variable Models | |

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Model Building: Models with Both Quantitative and Qualitative Variables | |

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Model Building: Comparing Nested Models | |

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Model Building: Stepwise Regression | |

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Residual Analysis: Checking the Regression Assumptions | |

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Some Pitfalls: Estimability, Multicollinearity, and Extrapolation | |

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Categorical Data Analysis | |

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Categorical Data and the Multinomial Distribution | |

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Testing Categorical Probabilities: One-Way Table | |

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Testing Categorical Probabilities: Two-Way (Contingency) Table | |

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A Word of Caution about Chi-Square Tests | |

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Nonparametric Statistics | |

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Introduction: Distribution-Free Tests | |

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Single Population Inferences: The Sign Test | |

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Comparing Two Populations: The Wilcoxon Rank Sum Test for Independent Samples | |

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Comparing Two Populations: The Wilcoxon Signed Rank Test for the Paired Difference Experiment | |

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The Kruskal-Wallis H-Test for a Completely Randomized Design | |

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The Friedman F r -Test for a Randomized Block Design | |

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Spearman''s Rank Correlation Coefficient | |

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Tables Random Numbers | |

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Binomial Probabilities | |

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Poisson Probabilities | |

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Normal Curve Areas | |

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Exponentials | |

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Critical Values of t | |

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Critical Values of hellip;c2 | |

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Percentage Points of the F Distribution, hellip;a= .10 | |

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Percentage Points of the F Distribution, hellip;a=.05 | |

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Percentage Points of the F Distribution, hellip;a=.025 | |

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Percentage Points of the F Distribution, hellip;a=.01 | |

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Critical Values of T L and T U for the Wilcoxon Rank Sum Test: Independent Samples | |

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Critical Values of T O in the Wilcoxon Paired Difference Signed Rank Test | |

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Critical Values of Spearman''s Rank Correlation Coefficient | |

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Data Sets | |

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Coronary Artery Patients'' Blood Loss Data | |

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Car & Driver Data | |

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Starting Salaries of USF Graduates | |

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Sealed Milk Bids Data | |

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Federal Trade Commission Rankings of Domestic Cigarette Brands | |

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Calculation Formulas for Analysis of Variance | |

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Short Answers to Selected Odd-Numbered Exercises | |

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Index | |