Statistics: Informed Decisions Using Data, Global Edition

<ul> <li>PART 1: GETTING THE INFORMATION YOU NEED </li> <li>&nbsp;1. Data Collection </li> <li>1.1 Introduction to the Practice of Statistics </li> <li>1.2 Observational Studies versus Designed Experiments </li> <li>1.3 Simple Random Sampling </li> <li>1.4 Other Effective Sampling Methods </li> <li>1.5 Bias in Sampling </li> <li>1.6 The Design of Experiments </li> <li>PART 2: DESCRIPTIVE STATISTICS </li> <li>2. Organizing and Summarizing Data </li> <li>2.1 Organizing Qualitative Data </li> <li>2.2 Organizing Quantitative Data: The Popular Displays </li> <li>2.3 Additional Displays of Quantitative Data </li> <li>2.4 Graphical Misrepresentations of Data </li> <li>3. Numerically Summarizing Data </li> <li>3.1 Measures of Central Tendency </li> <li>3.2 Measures of Dispersion </li> <li>3.3 Measures of Central Tendency and Dispersion from Grouped Data </li> <li>3.4 Measures of Position and Outliers </li> <li>3.5 The Five-Number Summary and Boxplots </li> <li>4. Describing the Relation between Two Variables </li> <li>4.1 Scatter Diagrams and Correlation </li> <li>4.2 Least-Squares Regression </li> <li>4.3 Diagnostics on the Least-Squares Regression Line </li> <li>4.4 Contingency Tables and Association </li> <li>4.5 Nonlinear Regression: Transformations (online) 4-1 </li> <li>PART 3: PROBABILITY AND PROBABILITY DISTRIBUTIONS </li> <li>5. Probability </li> <li>5.1 Probability Rules </li> <li>5.2 The Addition Rule and Complements </li> <li>5.3 Independence and the Multiplication Rule </li> <li>5.4 Conditional Probability and the General Multiplication Rule </li> <li>5.5 Counting Techniques </li> <li>5.6 Putting It Together: Which Method Do I Use? </li> <li>5.7 Bayes’s Rule (online) 5-1 </li> <li>6. Discrete Probability Distributions </li> <li>6.1 Discrete Random Variables </li> <li>6.2 The Binomial Probability Distribution </li> <li>6.3 The Poisson Probability Distribution </li> <li>6.4 The Hypergeometric Probability Distribution (online) 6-1 </li> <li>7. The Normal Probability Distribution </li> <li>7.1 Properties of the Normal Distribution </li> <li>7.2 Applications of the Normal Distribution </li> <li>7.3 Assessing Normality </li> <li>7.4 The Normal Approximation to the Binomial Probability Distribution </li> <li>PART 4: INFERENCE: FROM SAMPLES TO POPULATION </li> <li>8. Sampling Distributions </li> <li>8.1 Distribution of the Sample Mean </li> <li>8.2 Distribution of the Sample Proportion </li> <li>9. Estimating the Value of a Parameter </li> <li>9.1 Estimating a Population Proportion </li> <li>9.2 Estimating a Population Mean </li> <li>9.3 Estimating a Population Standard Deviation </li> <li>9.4 Putting It Together: Which Procedure Do I Use? </li> <li>9.5 Estimating with Bootstrapping </li> <li>10. Hypothesis Tests Regarding a Parameter </li> <li>10.1 The Language of Hypothesis Testing </li> <li>10.2 Hypothesis Tests for a Population Proportion </li> <li>10.3 Hypothesis Tests for a Population Mean </li> <li>10.4 Hypothesis Tests for a Population Standard Deviation </li> <li>10.5 Putting It Together: Which Method Do I Use? </li> <li>10.6 The Probability of a Type II Error and the Power of the Test </li> <li>11. Inferences on Two Samples </li> <li>11.1 Inference about Two Population Proportions </li> <li>11.2 Inference about Two Means: Dependent Samples </li> <li>11.3 Inference about Two Means: Independent Samples </li> <li>11.4 Inference about Two Population Standard Deviations </li> <li>11.5 Putting It Together: Which Method Do I Use? </li> <li>12. Inference on Categorical Data</li> </ul>