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所在平台: Udemy |
课程主页: https://www.udemy.com/course/correlation-and-linear-regression-with-stata-in-arabic/
课程评论：没有评论
**课程名称：** 利用Stata进行相关性和线性回归分析（阿拉伯语） **课程概述：** 本课程将教授您使用Stata进行相关性和线性回归分析的基础及高级技巧。课程共分为五个部分： 1. **引言：** 介绍Framingham数据集，这是一个自1948年以来被广泛引用的真实世界大型数据集，贯穿整个课程用于实际应用演示。 2. **相关分析：** 学习并应用相关分析，理解其三个关键参数：方向、强度和显著性。您将学习如何选择合适的检验方法并进行正确解读。此外，还将学习如何为数据可视化选择合适的图表。 3. **回归分析：** 专注于回归分析，通过简单线性回归和多元线性回归模型，运用连续型、分类型和有序型变量来回答现实研究问题。 4. **高级估计后分析：** 介绍交互作用、边际效应（margins）和边际效应图（margins plots）等高级估计后分析技术。课程中，每个概念都将通过独立视频讲解，并辅以实际Stata操作和真实数据集的演示。 5. **课程总结：** 对课程中的关键信息进行回顾和总结。
This course will teach you the fundamentals and advanced techniques for performing correlation and linear regression analyses with STATA in Arabic. The course is broken down into five sections.The first section is an introduction that includes a description of the Framingham dataset, a large real-world dataset that has been used in at least 3000 publications since 1948. Throughout the course, this dataset will be used for real-world applications.The second part of this course will concentrate on studying and learning how to apply correlation analysis and interpret its three parameters, including direction, strength, and significance, as well as how to choose the appropriate test and make the correct interpretation. Furthermore, for data visualization, you will learn how to use the appropriate graph to represent your data. The third section of this course will focus on regression analysis and its performance using simple linear regression and multiple linear regression models to answer real-world research questions. As continuous, categorical, and ordinal variables, various types of variables will be used.The fourth section will go over advanced post-estimation analysis techniques like interaction, margins, and margins plots. Separate videos will demonstrate a specific concept throughout the course, followed by actual STATA and real dataset implementation.The concluding section will include a summary of the course's essential information.
