(4)Teaching Methods and Approaches The main methods and approaches used in this Module is in-class teaching, multimedia teaching,network-assisted teaching,and class discussion. Module 6 Joint distributed random variables (1) Purpose and Requirements 1.To comprehend the idea and concept of joint distribution 2.To comprehend the concept of independence and independent random variable 3.To comprehend the concept of discrete conditional distributions 4.To comprehend the concept of continuous conditional distribution 5.Master the methods to compute joint distribution of random variables (2) Contents Section 1 1.Main Content:Joint distribution function,independent random variables and their sum,discrete conditional distributions,continuous conditional distributions,joint distribution of functions of random variables 2.Basic Concepts and Knowledge Points:Joint distribution,independence, discrete conditional distribution,continuous conditional distribution,joint distribution of functions 3.Problems and Application(Ability Requirements):The application of joint distribution.independence and conditional distribution. (3)Thinking and Practice Identify the situations in applications that we need to use joint distribution as models and use joint distribution function to solve some problems.Ideological and political education:How to quantitatively describe real-world phenomena. (4) Teaching Methods and Approaches The main methods and approaches used in this Module is in-class teaching multimedia teaching,network-assisted teaching,and class discussion. Module 7 Properties of Expectation (1)Purpose and Requirements 1.To master the computation ofexpectation of sums 2.To comprehend the concept of moment 3.To master the computation of covariance of sums 66 (4) Teaching Methods and Approaches The main methods and approaches used in this Module is in-class teaching, multimedia teaching, network-assisted teaching, and class discussion. Module 6 Joint distributed random variables (1) Purpose and Requirements 1．To comprehend the idea and concept of joint distribution 2．To comprehend the concept of independence and independent random variable 3．To comprehend the concept of discrete conditional distributions 4．To comprehend the concept of continuous conditional distributions 5．Master the methods to compute joint distribution of random variables (2) Contents Section 1 1．Main Content: Joint distribution function, independent random variables and their sum, discrete conditional distributions, continuous conditional distributions, joint distribution of functions of random variables 2．Basic Concepts and Knowledge Points: Joint distribution, independence, discrete conditional distribution, continuous conditional distribution, joint distribution of functions 3．Problems and Application (Ability Requirements): The application of joint distribution, independence and conditional distribution. (3) Thinking and Practice Identify the situations in applications that we need to use joint distribution as models and use joint distribution function to solve some problems. Ideological and political education: How to quantitatively describe real-world phenomena. (4) Teaching Methods and Approaches The main methods and approaches used in this Module is in-class teaching, multimedia teaching, network-assisted teaching, and class discussion. Module 7 Properties of Expectation (1) Purpose and Requirements 1．To master the computation of expectation of sums 2．To comprehend the concept of moment 3．To master the computation of covariance of sums