Parameter estimation test content: the concept of point estimation; Estimator and estimated value; Moment estimation method; Maximum likelihood estimation method. The investigation of moment estimation and likelihood estimation in parameter estimation combines the numerical characteristics in chapter 4, so we should be familiar with the calculation methods and definitions of numerical characteristics in chapter 4.

Examination requirements:

1. Understand the concepts of point estimation, estimator and parameter estimation.

2. Master moment estimation methods (first-order moment and second-order moment) and maximum likelihood estimation methods.

Extended data:

Number three postgraduate entrance examination, the examination content of probability theory:

1, random events and probability

2. Random variables and their distribution

3. Multidimensional random variables and their distribution

4. Digital characteristics of random variables

5. Law of Large Numbers and Central Limit Theorem

6. Basic concepts of mathematical statistics

7. Parameter estimation

Baidu Encyclopedia-Three Outline of Postgraduate Mathematics

Research Network -20 19 Interpretation of Mathematics Outline for Postgraduate Entrance Examination and Prediction of Important Knowledge Points: Probability