The Science Of Being Great

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For courses in introductory statistics. This is the 18-week standalone access card for MyLab Statistics. The art and science of learning from data Statistics: The Art and Science of Learning from Data takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises. The authors believe that it's important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data. The 5th Edition enhances the student and instructor experience and provides a more accessible introduction to statistical thinking and practice. Personalize learning with MyLab Statistics MyLab™ Statistics is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch®, integrated web-based statistical software, students learn the skills they need to interact with data in the real world. 0136559891 / 9780136559894 MYLAB STATISTICS WITH PEARSON ETEXT -- ACCESS CARD -- FOR STATISTICS: THE ART AND SCIENCE OF LEARNING FROM DATA (18-WEEKS), 5/e Cover Title Page Copyright Dedication Contents An Introduction to the Web Apps Preface About the Authors Part One: Gathering and Exploring Data Chapter 1. Statistics: The Art and Science of Learning From Data 1.1 Using Data to Answer Statistical Questions 1.2 Sample Versus Population 1.3 Organizing Data, Statistical Software, and the New Field of Data Science Chapter Summary Chapter Exercises Chapter 2. Exploring Data With Graphs and Numerical Summaries 2.1 Different Types of Data 2.2 Graphical Summaries of Data 2.3 Measuring the Center of Quantitative Data 2.4 Measuring the Variability of Quantitative Data 2.5 Using Measures of Position to Describe Variability 2.6 Linear Transformations and Standardizing 2.7 Recognizing and Avoiding Misuses of Graphical Summaries Chapter Summary Chapter Exercises Chapter 3. Exploring Relationships Between Two Variables 3.1 The Association Between Two Categorical Variables 3.2 The Relationship Between Two Quantitative Variables 3.3 Linear Regression: Predicting the Outcome of a Variable 3.4 Cautions in Analyzing Associations Chapter Summary Chapter Exercises Chapter 4. Gathering Data 4.1 Experimental and Observational Studies 4.2 Good and Poor Ways to Sample 4.3 Good and Poor Ways to Experiment 4.4 Other Ways to Conduct Experimental and Nonexperimental Studies Chapter Summary Chapter Exercises Part Two: Probability, Probability Distributions, and Sampling Distributions Chapter 5. Probability in Our DailyLives 5.1 How Probability Quantifies Randomness 5.2 Finding Probabilities 5.3 Conditional Probability 5.4 Applying the Probability Rules Chapter Summary Chapter Exercises Chapter 6. Random Variables and Probability Distributions 6.1 Summarizing Possible Outcomes and Their Probabilities 6.2 Probabilities for Bell-Shaped Distributions: The Normal Distribution 6.3 Probabilities When Each Observation Has Two Possible Outcomes: The Binomial Distribution Chapter Summary Chapter Exercises Chapter 7. Sampling Distributions 7.1 How Sample Proportions Vary Around the Population Proportion 7.2 How Sample Means Vary Around the Population Mean 7.3 Using the Bootstrap to Find Sampling Distributions Chapter Summary Chapter Exercises Part Three: Inferential Statistics Chapter 8. Statistical Inference: Confidence Intervals 8.1 Point and Interval Estimates of Population Parameters 8.2 Confidence Interval for a Population Proportion 8.3 Confidence Interval for a Population Mean 8.4 Bootstrap Confidence Intervals Chapter Summary Chapter Exercises Chapter 9. Statistical Inference: Significance Tests About Hypotheses 9.1 Steps for Performing a Significance Test 9.2 Significance Test About a Proportion 9.3 Significance Test About a Mean 9.4 Decisions and Types of Errors in Significance Tests 9.5 Limitations of Significance Tests 9.6 The Likelihood of a Type II Error and the Power of a Test Chapter Summary Chapter Exercises Chapter 10. Comparing Two Groups 10.1 Categorical Response: Comparing Two Proportions 10.2 Quantitative Response: Comparing Two Means 10.3 Comparing Two Groups With Bootstrap or Permutation Resampling 10.4 Analyzing Dependent Samples 10.5 Adjusting for the Effects of Other Variables Chapter Summary Chapter Exercises Part Four: Extended Statistical Methods and Models for Analyzing Categorical and Quantitative Variables Chapter 11. Categorical Data Analysis 11.1 Independence and Dependence (Association) 11.2 Testing Categorical Variables for Independence 11.3 Determining the Strength of the Association 11.4 Using Residuals to Reveal the Pattern of Association 11.5 Fisher’s Exact and Permutation Tests Chapter Summary Chapter Exercises Chapter 12. Regression Analysis 12.1 The Linear Regression Model 12.2 Inference About Model Parameters and the Relationship 12.3 Describing the Strength of the Relationship 12.4 How the Data Vary Around the Regression Line 12.5 Exponential Regression: A Model for Nonlinearity Chapter Summary Chapter Exercises Chapter 13. Multiple Regression 13.1 Using Several Variables to Predict a Response 13.2 Extending the Correlation Coefficient and R2 for Multiple Regression 13.3 Inferences Using Multiple Regression 13.4 Checking a Regression Model Using Residual Plots 13.5 Regression and Categorical Predictors 13.6 Modeling a Categorical Response: Logistic Regression Chapter Summary Chapter Exercises Chapter 14. Comparing Groups: Analysis of Variance Methods 14.1 One-Way ANOVA: Comparing Several Means 14.2 Estimating Differences in Groups for a Single Factor 14.3 Two-Way ANOVA: Exploring Two Factors and Their Interaction Chapter Summary Chapter Exercises Chapter 15. Nonparametric Statistics 15.1 Compare Two Groups by Ranking 15.2 Nonparametric Methods for Several Groups and for Dependent Samples Chapter Summary Chapter Exercises Appendix Answers Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Index of Applications A B C D E F G H I J K L M N O P Q R S T U V W Credits This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For courses in introductory statistics. This is the 18-week standalone access card for MyLab Statistics. The art and science of learning from data Statistics: The Art and Science of Learning from Data takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises. The authors believe that it's important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data. The 5th Edition enhances the student and instructor experience and provides a more accessible introduction to statistical thinking and practice. Personalize learning with MyLab Statistics MyLabTM Statistics is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch®, integrated web-based statistical software, students learn the skills they need to interact with data in the real world. 0136559891 / 9780136559894 MYLAB STATISTICS WITH PEARSON ETEXT -- ACCESS CARD -- FOR STATISTICS: THE ART AND SCIENCE OF LEARNING FROM DATA (18-WEEKS), 5/e "One of our goals in writing this book was to help make the conceptual approach more interesting and more readily accessible to students. At the end of the course, we want students to look back at their statistics course and realize that they learned practical concepts that will serve them well for the rest of their lives. We also want students to come to appreciate that in practice, assumptions are not perfectly satisfied, models are not exactly correct, distributions are not exactly normally distributed, and different factors should be considered in conducting a statistical analysis. The title of our book reflects the experience of data analysts, who soon realize that statistics is an art as well as a science"-- Provided by publisher