Statistics, Data, and Statistical Thinking | |

The Science of Statistics | |

Types of Statistical Applications | |

Fundamental Elements of Statistics | |

Types of Data | |

Collecting Data | |

The Role of Statistics in Critical Thinking | |

Methods for Describing Sets of Data | |

Describing Qualitative Data | |

Graphical Methods for Describing Quantitative Data | |

Summation Notation | |

Numerical Measures of Central Tendency | |

Numerical Measures of Variability | |

Interpreting the Standard Deviation | |

Numerical Measures of Relative Standing | |

Methods for Detecting Outliers (Optional) | |

Graphing Bivariate Relationships (Optional) | |

Distorting the Truth with Descriptive Techniques | |

Probability | |

Events, Sample Spaces, and Probability | |

Unions and Intersections | |

Complementary Events | |

The Additive Rule and Mutually Exclusive Events | |

Conditional Probability | |

The Multiplicative Rule and Independent Events | |

Random Sampling | |

Some Counting Rules (Optional) | |

Discrete Random Variables | |

Two Types of Random Variables | |

Probability Distributions for Discrete Random Variables | |

Expected Values of Discrete Random Variables | |

The Binomial Random Variable | |

The Poisson Random Variable (Optional) | |

The Hypergeometric Random Variable (Optional) | |

Continuous Random Variables | |

Continuous Probability Distributions | |

The Uniform Distribution | |

The Normal Distribution | |

Descriptive Methods for Assessing Normality | |

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

The Exponential Distribution (Optional) | |

Sampling Distributions | |

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

Unbiasedness and Minimum Variance (Optional) | |

The Central Limit Theorem | |

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

Large-Sample Confidence Interval for a Population Mean | |

Small-Sample Confidence Interval for a Population Mean | |

Large-Sample Confidence Interval for a Population Proportion | |

Determining the Sample Size | |

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

The Elements of a Test of Hypothesis | |

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

Observed Significance Levels: p-Values | |

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

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

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

Test of Hypothesis about a Population Proportion | |

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

Comparing Two Population Means: Independent Sampling | |

Comparing Two Population Means: Paired Difference Experiments | |

Comparing Two Population Proportions: Independent Sampling | |

Determining the Sample Size | |

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

Analysis of Variance: Comparing More Than Two Means | |

Elements of a Designed Experiment | |

The Completely Randomized Design | |

Multiple Comparisons of Means | |

The Randomized Block Design | |

Factorial Experiments | |

Simple Linear Regression | |

Probabalistic Models | |

Fitting the Model: The Least Squares Approach | |

Model Assumptions | |

An Estimator of hellip;s2 | |

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

The Coefficient of Correlation | |

The Coefficient of Determination | |

Using the Model for Estimation and Prediction | |

A Complete Example | |

Multiple Regression and Model Building | |

Multiple Regression Models | |

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

Model Assumptions | |

Inferences About the Individual hellip;b Parameters | |

Checking the Overall Utility of a Model | |

Using the Model for Estimation and Prediction | |

Model Building: Interaction Models | |

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

Model Building: Qualitative (Dummy) Variable Models | |

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

Model Building: Comparing Nested Models | |

Model Building: Stepwise Regression | |

Residual Analysis: Checking the Regression Assumptions | |

Some Pitfalls: Estimability, Multicollinearity, and Extrapolation | |

Categorical Data Analysis | |

Categorical Data and the Multinomial Distribution | |

Testing Categorical Probabilities: One-Way Table | |

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

A Word of Caution about Chi-Square Tests | |

Nonparametric Statistics | |

Introduction: Distribution-Free Tests | |

Single Population Inferences: The Sign Test | |

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

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

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

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

Spearman''s Rank Correlation Coefficient | |

Tables Random Numbers | |

Binomial Probabilities | |

Poisson Probabilities | |

Normal Curve Areas | |

Exponentials | |

Critical Values of t | |

Critical Values of hellip;c2 | |

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

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

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

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

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

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

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

Data Sets | |

Coronary Artery Patients'' Blood Loss Data | |

Car & Driver Data | |

Starting Salaries of USF Graduates | |

Sealed Milk Bids Data | |

Federal Trade Commission Rankings of Domestic Cigarette Brands | |

Calculation Formulas for Analysis of Variance | |

Short Answers to Selected Odd-Numbered Exercises | |

Index | |

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