Name: Statistics, Binder Ready Version: Unlocking the Power of Data
Author: Robin H. Lock, Patti Frazer Lock, Kari Lock Morgan, Eric F. Lock, Dennis F. Lock
ISBN: 9781119163664

Chapter 1.1 - The Structure Of Data Chapter 1.2 - Sampling From A Population Chapter 1.3 - Experiments And Observational Studies Chapter 2.1 - Categorical Variables Chapter 2.2 - One Quantitative Variable: Shape And Center Chapter 2.3 - One Quantitative Variable: Measures Of Spread Chapter 2.4 - Boxplots And Quantitative/categorical Relationships Chapter 2.5 - Two Quantitative Variables: Scatterplot And Correlation Chapter 2.6 - Two Quantitative Variables: Linear Regression Chapter 2.7 - Data Visualization And Multiple Variables

Chapter A - Essential Synthesis Chapter 3.1 - Sampling Distributions Chapter 3.2 - Understanding And Interpreting Confidence Intervals Chapter 3.3 - Constructing Bootstrap Confidence Intervals Chapter 3.4 - Bootstrap Confidence Intervals Using Percentiles Chapter 4.1 - Introducing Hypothesis Tests Chapter 4.2 - Measuring Evidence With P-values Chapter 4.3 - Determining Statistical Significance Chapter 4.4 - A Closer Look At Testing Chapter 4.5 - Making Connections Chapter B - Essential Synthesis Chapter 5.1 - Hypothesis Tests Using Normal Distributions Chapter 5.2 - Confidence Intervals Using Normal Distributions Chapter 6.1 - Inference For A Proportion Chapter 6.2 - Inference For A Mean Chapter 6.3 - Inference For A Difference In Proportions Chapter 6.4 - Inference For A Difference In Means Chapter 6.5 - Paired Difference In Means Chapter C - Essential Synthesis Chapter 7.1 - Testing Goodness-of-fit For A Single Categorical Variable Chapter 7.2 - Testing For An Association Between Two Categorical Variables Chapter 8.1 - Analysis Of Variance Chapter 8.2 - Pairwise Comparisons And Inference After Anova Chapter 9.1 - Inference For Slope And Correlation Chapter 9.2 - Anova For Regression Chapter 9.3 - Confidence And Prediction Intervals Chapter 10.1 - Multiple Predictors Chapter 10.2 - Checking Conditions For A Regression Model Chapter 10.3 - Using Multiple Regression Chapter D - Essential Synthesis Chapter E - The Big Picture: Essential Synthesis Chapter P.1 - Probability Rules Chapter P.2 - Tree Diagrams And Bayes’ Rule Chapter P.3 - Random Variables And Probability Functions Chapter P.4 - Binomial Probabilities Chapter P.5 - Density Curves And The Normal Distribution

Book Details

Statistics: Unlocking the Power of Data, 2nd Edition Loose-leaf Print Companion continues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference. These methods are brought to life through authentically relevant examples, enabled through easy to use statistical software, and are accessible at very early stages of a course. The program includes the more traditional methods like t-tests, chi-square texts, etc. but only after students have developed a strong intuitive understanding of inference through randomization methods. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The program is driven by real data and real applications.