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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.