4. Statistics and Probability

1. Exploring Univariate and Bivariate Data (S1)
2. Sampling and Study Design (S2)
3. Probability Models (S3)
4. Sampling Distributions (S4)
5. Point and Interval Estimation (S5)
6. Significance Testing (S6)
7. Inference for Regression (S7)
8. Assessing Assumptions of Statistical Models (S8)

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High School

1. Point and Interval Estimation
   1. Overview of Point Estimation
      When a parameter is being estimated, the estimate can be either a single number or it can be a range of scores. When the estimate is a single number, the estimate is called a "point estimate"; when the estimate is a range of scores, the estimate is called an interval estimate. Confidence intervals are used for interval estimates.
   2. Point Estimation
      Point estimation refers to the process of estimating a parameter from a probability distribution, based on observed data from the distribution. It is one of the core topics in mathematical statistics. In this chapter, we will explore the most common methods of point estimation: the method of moments, the method of maximum likelihood, and Bayes' estimators. We also study important properties of estimators, including sufficiency and completeness, and the basic question of whether an estimator is the best possible one.