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| The Role of Statistics and the Data Analysis Process | |
| Three Reasons to Study Statistics | |
| The Nature and Role of Variability | |
| Statistics and the Data Analysis Process | |
| Types of Data and Some Simple Graphical Displays | |
| Collecting Data Sensibly | |
| Statistical Studies: Observation and Experimentation | |
| Sampling | |
| Simple Comparative Experimen... MORE | |
| More Experimental Design | |
| More on Observational Studies: Designing Surveys | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Graphical Methods for Describing Data | |
| Displaying Categorical Data: Comparative Bar Charts and Pie Charts | |
| Displaying Numerical Data: Stem-and-Leaf Displays | |
| Displaying Numerical Data: Frequency Distributions and Histograms | |
| Displaying Bivariate Numerical Data | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Numerical Methods for Describing Data | |
| Describing the Center of a Data Set | |
| Describing the Variability in a Data Set | |
| Summarizing a Data Set: Boxplots | |
| Interpreting Center and Variability: Chebyshev's Rule, the Empirical Rule, and z Scores | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Summarizing Bivariate Data | |
| Correlation | |
| Linear Regression: Fitting a Line to Bivariate Data | |
| Assessing the Fit of a Line | |
| Nonlinear Relationship and Transformations | |
| Logistic Regression | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Probability | |
| Interpreting Probabilities and Basic Probability Rules | |
| Probability as a Basis for Making Decisions | |
| Estimating Probabilities Empirically and by Using Simulation | |
| Population Distributions | |
| Describing the Distribution of Values in a Population | |
| Population Models for Continuous Numerical Variables | |
| Normal Distributions | |
| Checking for Normality and Normalizing Transformations | |
| Sampling Variability and Sampling Distributions | |
| Statistics and Sampling Variability | |
| The Sampling Distribution of a Sample Mean | |
| The Sampling Distribution of a Sample Proportion | |
| Estimation Using a Single Sample | |
| Point Estimation | |
| Large-Sample Confidence Interval for a Population Proportion | |
| Confidence Interval for a Population Mean | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Hypotheses Testing Using a Single Sample | |
| Hypotheses and Test Procedures | |
| Errors in Hypothesis Testing | |
| Large-Sample Hypothesis Tests for a Population Proportion | |
| Hypothesis Test for a Population Mean | |
| Power and Probability of Type II Error | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Comparing Two Populations or Treatments | |
| Inferences Concerning the Difference Between Two Population or Treatment Means Using Independent Samples | |
| Inferences Concerning the Difference Between Two Population or Treatment Means Using Paired Samples | |
| Large Sample Inferences Concerning a Difference Between Two Population or Treatment Proportions | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| The Analysis of Categorical Data and Doogness-of-Fit Tests | |
| Chi-Square Tests for Univariate Data | |
| Tests for Homogeneity and Independence in a Two-way Table | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Simple Linear Regression and Correlation Inferential Methods | |
| Simple Linear Regression Model | |
| Inferences About the Slope of the Population Regression Line | |
| Checking Model Adequacy | |
| Inferences Based on the Estimated Regression Line | |
| Inferences About the Population Correlation Coefficient | |
| Interpreting and Communicating the Results of Statistical Analyses | |
| Multiple Regression Analysis | |
| Multiple Regression Models | |
| Fitting a Model and Assessing Its Utility | |
| Inferences Based on an Estimated Model | |
| Other Issues in Multiple Regression | |
| Interpreting and C | |
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