15.3 Bayesian model for world population.15.1 Read in and prepare the data for analysis.15 Extended Example: World Population Data.12.4 Extended example: predicting call centre wait times.12.3 Bayesian Prediction: coin flipping.11.3.2 Setting Hyperparameters by moment-matching.11.2 Estimation in Bayesian Inference: point and interval estimation.11.1 Estimation in Bayesian Inference: general ideas.
10.2.3 Testing goodness of fit: simulation.10 Extended Example: Reasoning About Goodness of Fit.9.1.4 Gross calorific value measurements for Daw Mill 258GB41.9.1.2 Gross calorific value measurements for Osterfeld 262DE27.9.1 Confidence Intervals for the Mean (Chapter 23).9 Confidence Intervals and Quantifying Uncertainty.8.2 Extended example: rental housing in Toronto.8.1.3 Example: unknown coins, \(n\) bigger than \(2\).7.1.3 Extended example: the standard error of a proportion.7.1.2 Parametric Bootstrap: software data.7.1.1 Empirical bootstrap: Old Faithful data.6.1.1 Frequentist/Likelihood Perspective.5 Evaluating Estimators: Efficiency and Mean Squared Error.4.1.2 Extended example: TTC ridership revenues.3.2.1 Extended example: the probability of heads.3.1.1 Extended example: the probability of heads.3 Introduction to Statistics: Law of Large Numbers and Central Limit Theorem.2.5.4 Analysis III: trends in quality over time.2.5.3 Analysis II: Do different wards have different quality housing?.2.5.2 Analysis I: what does the data look like?.2.5 Case study: rental housing in Toronto.2.4.2 Association between smoking and mortality.2.4 Extended example: smoking and age and mortality.2 Introduction to Data Analysis: Data Input and Basic Summaries.
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