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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introductory-econometrics-i/
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课程名称：计量经济学导论 课程概述：本课程全面介绍了“计量经济学导论”，旨在为全球各大中专院校的高中本科生提供计量经济学的基础知识。我们在“救主学院”欢迎您加入，重点关注“计量经济学导论”中从考试角度来看最重要的概念，包括“统计回顾”、“经典线性回归模型（CLRM）”、“多元线性回归模型（MLRM）”、“异方差性”、“自相关”以及“多重共线性”的“成因与后果”、“杜宾-沃森检验”、“怀特检验”、“最小二乘法（OLS）”及“模型规范分析”。课程将利用技术工具和教育软件，并结合大量自解释的三维图表，彻底改变智能课堂的授课方式。 计量经济学是将统计方法应用于经济数据，以给予经济关系以实证内容。更准确地说，它是“基于理论与观察的并行发展，通过适当的推断方法，对实际经济现象进行定量分析”。多元线性回归模型是计量经济学的基本工具。计量经济学理论利用统计理论和数理统计来评估和发展计量经济学方法。计量经济学家努力寻找具有理想统计特性的估计量，包括无偏性、有效性和一致性。 此课程旨在帮助学生掌握计量经济学的基本原理和工具，进而分析实际经济问题。
A comprehensive study on 'Introductory Econometrics' is designed keeping in mind the Principles of Econometrics as part of syllabus covered for high school undergraduates at central universities in different parts of the world. At 'The Saviour Academy', we welcome you all to learn such a platform wherein we'll be focusing upon the most important concepts from the examination perspective used under 'Introductory Econometrics' such as "Review of Statistics", "Classical Linear Regression Model (CLRM)", "Multiple l Linear Regression Model (MLRM)", "Heteroscadasticity","Autocorrelation" as well as "Multicollinearity" like its "Causes & Consequences", "Durbin-Watson Test", "White's Test", "OLS Methods of Least Squares" and "Specification Analyses" with the help of technical tools, educational software and indeed with a lot of self-explanatory diagrams in a three-dimensional platform and then we say it had revolutionized the method of smart classes very well.Econometrics is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". A basic tool for econometrics is the multiple linear regression model. Econometric theory uses statistical theory and mathematical statistics to evaluate and develop econometric methods. Econometricians try to find estimators that have desirable statistical properties including unbiasedness, efficiency, and consistency.
