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Mathematics one postgraduate entrance examination outline
Generally speaking, No.1 is divided into advanced mathematics, linear algebra and probability theory, with a total score of 150, in which advanced mathematics accounts for about 90 points, linear algebra 30 points and probability theory 30 points. * * * There are three kinds of questions, ten multiple-choice questions have six highs and two lines and two probability theories, fill-in-the-blank questions have four highs and one line and one probability theory, and six solution questions have four highs and one line and one probability theory.

massive

Limit, Continuity, Integral: We need to fully understand and master some definitions, and train and use the questions flexibly through the definitions.

One-dimensional and multivariate function calculus: This aspect needs to summarize and understand a system, because the whole calculus starts from this, and sort out the system.

Infinite series and ordinary differential equations: such as variable upper bound definite integral, variable integral domain double integral, necessary and sufficient conditions of total differential, etc. It's all difficult places to set up, so pay more attention.

Infinite series training

Calculus proof and inequality, sequence limit, etc. The difficulty of number one can also be said to be the most difficult knowledge point in the whole test paper, so there is no need to solve such problems with a must-do mentality.

vector generation

Linear equations: including the solution structure of homogeneous and non-homogeneous linear equations, the solution and proof of basic solution system, etc. Generally speaking, it is not difficult, and it can be made by ordinary methods.

Similarity of matrix: it is often the similarity diagonalization of matrix, which is easy to combine with big questions, with strong knowledge flexibility and high comprehensiveness.

Similar diagonal notes

? probability theory

Random variables: Generally speaking, there are many concepts and less calculation, which requires a deep grasp of concepts.

Estimation and test: mainly the principles and methods of maximum likelihood estimation and hypothesis test.