Ron Larson received his Ph.D. in mathematics from the University of Colorado in 1970. At that time he accepted a position with Penn State University, and he currently holds the rank of professor of mathematics at the university. Larson is the lead author of more than two dozen mathematics textbooks that range from 6th grade through calculus levels. Many of his texts, such as the 10th edition of his calculus text, are leaders in their markets. Larson is also one of the pioneers in the use of multimedia and the Internet to enhance the learning of mathematics. He has authored multimedia programs, extending from the elementary school through calculus levels. Larson is a member of several professional groups and is a frequent speaker at national and regional mathematics meetings. Many thanks to Betsy Farber for her significant contributions to previous editions of the text. Sadly, Betsy passed away in 2013. She received her Bachelor’s degree in mathematics from Penn State University and her Master’s degree in mathematics from the College of New Jersey. Betsy taught all levels of mathematics at Bucks County Community College in Newtown, Pennsylvania for many years. She made many notable contributions throughout her career to developing new ways to make statistics relevant and interesting for both online and traditional students.

• I. DESCRIPTIVE STATISTICS Introduction to Statistics 1.1 An Overview of Statistics1.2 Data Classification1.3 Data Collection and Experimental DesignDescriptive Statistics 2.1 Frequency Distributions and Their Graphs2.2 More Graphs and Displays2.3 Measures of Central Tendency2.4 Measures of Variation2.5 Measures of PositionII. PROBABILITY AND PROBABILITY DISTRIBUTIONS Probability 3.1 Basic Concepts of Probability and Counting3.2 Conditional Probability and the Multiplication Rule3.3 The Addition Rule3.4 Additional Topics in Probability and CountingDiscrete Probability Distributions 4.1 Probability Distributions4.2 Binomial Distributions4.3 More Discrete Probability DistributionsNormal Probability Distributions 5.1 Introduction to Normal Distributions and the Standard Normal Distribution5.2 Normal Distributions: Finding Probabilities5.3 Normal Distributions: Finding Values5.4 Sampling Distributions and the Central Limit Theorem5.5 Normal Approximations to Binomial DistributionsIII. STATISTICAL INFERENCE Confidence Intervals 6.1 Confidence Intervals for the Mean (S Known)6.2 Confidence Intervals for the Mean (S Unknown)6.3 Confidence Intervals for Population Proportions6.4 Confidence Intervals for Variance and Standard DeviationHypothesis Testing with One Sample 7.1 Introduction to Hypothesis Testing7.2 Hypothesis Testing for the Mean (S Known)7.3 Hypothesis Testing for the Mean (S Unknown)7.4 Hypothesis Testing for Proportions7.5 Hypothesis Testing for Variance and Standard DeviationHypothesis Testing with Two Samples 8.1 Testing the Difference Between Means (Independent Samples, S1 and S2 Known)8.2 Testing the Difference Between Means (Independent Samples, S1 and S2 Unknown)8.3 Testing the Difference Between Means (Dependent Samples)8.4 Testing the Difference Between ProportionsIV. MORE STATISTICAL INFERENCE Correlation and Regression 9.1 Correlation9.2 Linear Regression9.3 Measures of Regression and Prediction Intervals9.4 Multiple RegressionChi-Square Tests and the F-Distribution 10.1 Goodness-of-Fit Test10.2 Independence10.3 Comparing Two Variances10.4 Analysis of VarianceNonparametric Tests (Web Only)* 11.1 The Sign Test11.2 The Wilcoxon Tests11.3 The Kruskal-Wallis Test11.4 Rank Correlation11.5 The Runs Test * Available at www.pearson.com/math-stats-resources and in MyLab Statistics.APPENDICES A. Alternative Presentation of the Standard Normal DistributionB. TablesC. Normal Probability Plots