Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing.
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约翰霍普金斯大学课程信息
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完成时间大约为54 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
您将学到的内容有
Use regression analysis, least squares and inference
Understand ANOVA and ANCOVA model cases
Investigate analysis of residuals and variability
Describe novel uses of regression models such as scatterplot smoothing
您将获得的技能
- Model Selection
- Generalized Linear Model
- Linear Regression
- Regression Analysis
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
完成时间大约为54 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
提供方
约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
授课大纲 - 您将从这门课程中学到什么
完成时间为 13 小时
Week 1: Least Squares and Linear Regression
This week, we focus on least squares and linear regression.
完成时间为 13 小时
9 个视频 （总计 74 分钟）, 11 个阅读材料, 4 个测验
完成时间为 11 小时
Week 2: Linear Regression & Multivariable Regression
This week, we will work through the remainder of linear regression and then turn to the first part of multivariable regression.
完成时间为 11 小时
10 个视频 （总计 70 分钟）, 5 个阅读材料, 4 个测验
完成时间为 14 小时
Week 3: Multivariable Regression, Residuals, & Diagnostics
This week, we'll build on last week's introduction to multivariable regression with some examples and then cover residuals, diagnostics, variance inflation, and model comparison.
完成时间为 14 小时
14 个视频 （总计 168 分钟）, 5 个阅读材料, 5 个测验
完成时间为 16 小时
Week 4: Logistic Regression and Poisson Regression
This week, we will work on generalized linear models, including binary outcomes and Poisson regression.
完成时间为 16 小时
7 个视频 （总计 95 分钟）, 6 个阅读材料, 6 个测验
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来自回归模型的热门评论
由 KA 提供Dec 16, 2017
Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.
由 DA 提供Mar 10, 2019
This module was the maximum. I learned how powerful the use of Regression Models techniques in Data Science analysis is. I thank Professor Brian Caffo for sharing his knowledge with us. Thank you!
由 AW 提供Feb 19, 2018
Great subject, was a bit frustrated with some of the material (seemed rushed and not well prepared). Great assignment, but too restrictive on the max number of pages allowed. Wasted a lot of time.
由 AC 提供Aug 10, 2017
Regression analysis is something that is kind of easy for people to understand (outcome and predictor - people get that!). It's easy to explain to people. So much practice using the lm function!
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