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所在平台: Udemy |
课程主页: https://www.udemy.com/course/linear-regression-using-stata/
课程评论：没有评论
课程名称：使用Stata进行线性回归 课程概述： 本课程包含电子书和一套幻灯片，分为两个部分。第一部分介绍线性回归的理论，以直观的方式进行讲解，除了少量的加减法方程外不涉及复杂数学。此部分的目的是让学生理解线性回归的概念及其使用场景。学生将学习简单线性回归与多重线性回归之间的区别，理解线性回归的输出，测试模型的准确性和假设。课程中还将教学生如何在模型中包含不同类型的变量，如分类变量和二次变量。所有理论内容通过幻灯片和电子书进行传授，电子书对注册课程的学生免费提供。 第二部分课程将学习如何利用Stata应用所学知识。在这一部分中，学生将使用Stata拟合多重回归模型，生成描述模型拟合度和假设的图表，并使用特定变量命令使输出更易读。此部分课程假设学生具备Stata的基础知识。 这个课程适合对线性回归和Stata有兴趣的学习者，是了解和实践线性回归分析的良好起点。
Included in this course is an e-book and a set of slides. The course is divided into two parts. In the first part, students are introduced to the theory behind linear regression. The theory is explained in an intuitive way. No math is involved other than a few equations in which addition and subtraction are used. The purpose of this part of the course is for students to understand what linear regression is and when it is used. Students will learn the differences between simple linear regression and multiple linear regression. They will be able to understand the output of linear regression, test model accuracy and assumptions. Students will also learn how to include different types of variables in the model, such as categorical variables and quadratic variables. All this theory is explained in the slides, which are made available to the students, as well as in the e-book that is freely available for students who enroll in the course.In the second part of the course, students will learn how to apply what they learned using Stata. In this part, students will use Stata to fit multiple regression models, produce graphs that describe model fit and assumptions, and to use variable specific commands that will make the output more readable. This part assumed very basic knowledge of Stata.
