Regression Modeling in Practice

开始时间: 05/23/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/regression-modeling-practice

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课程详情

This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you.

实践中的回归建模:本课程重点介绍数据分析库中最重要的工具之一:回归分析。使用SAS或Python,您将从线性回归开始,然后学习如何在两个变量之间没有明确的线性关系时进行调整。您将检查结果的多个预测变量,并能够识别令人困惑的变量,这些变量可以告诉您有关结果的更具说服力的故事。您将学习回归分析的基础假设,如何解释回归系数以及如何使用回归诊断图和其他工具来评估回归模型的质量。在整个课程中,您将与其他人分享您开发的回归模型以及他们告诉您的故事。

课程大纲

This session starts where the Data Analysis Tools course left off. This first set of videos provides you with some conceptual background about the major types of data you may work with, which will increase your competence in choosing the statistical analysis that’s most appropriate given the structure of your data, and in understanding the limitations of your data set. We also introduce you to the concept of confounding variables, which are variables that may be the reason for the association between your explanatory and response variable. Finally, you will gain experience in describing your data by writing about your sample, the study data collection procedures, and your measures and data management steps.

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课程简介

这门课程关注的是数据分析以及机器学习领域的最重要的一个概念和工具:回归(模型)分析。这门课程使用SAS或者Python,从线性回归开始学习,到了解整个回归模型,以及应用回归模型进行数据分析。

课程标签

回归 回归模型 机器学习 Python sas

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