學生對 约翰霍普金斯大学 提供的 回归模型 的評價和反饋

4.4
3,263 個評分
561 條評論

課程概述

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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KA
2017年12月16日

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.

BA
2017年1月31日

It really helped me to have a better understanding of these Regression Models. However, I've noticed that there is a video recording repeated: Week 3, Model Selection. Part 3 is included in Part 2.

351 - 回归模型 的 375 個評論（共 542 個）

2017年10月23日

Brian did better job in this course to elaborate and demonstrate with examples. No doubt Brian is extremely knowledge about this subject. Once again, this and Statistical Inference courses are very challenging to truly completed with insightful understanding. That's why I take one star away.

2017年3月14日

The concepts are well explained and precise. I think it depends on the individual to dive deeper into the topic by independent learning. Good data examples. Also following the suggested book of the author helps with some extra excercises. However , I feel extra practice questions would help .

2016年6月3日

This course will give you a good basic foundation in regression models. However, do be prepared to do a good amount of work besides just viewing the videos. I would recommend at the very least to go through the exercises in the 'recommended textbook' to gain a better understanding.

2018年8月8日

You will need to know the subject before taking this class in order to understand or be able to put in a large amount of time to learn. The book "Introduction to Statistical Learning" is an excellent supplement to the course. Rigorous and rewarding when you put the work in.

2021年3月31日

The course materials are engaging and thorough and the quizzes are at a reasonable level of difficulty. The concluding course project instructions are unclear and it takes some creative thinking to understand how to fully relate these to the course content.

2016年11月14日

Regression models was almost just as difficult as statistical inference. Again, the swirls and exercises were of great help. The pace, as always, was quite fast, but in the end all the pieces fitted together. Congratulations on a job well done!

2016年2月10日

First 3 weeks give very reasonable overview of the subject - topics of linear / polynomial / multivariate regression are covered quite well.

Week 4 is a bit sloppy and ad-hoc, comparing to first 3 weeks - GLMs are given poorly.

2016年9月28日

It is a good course for learning regression model implementation in R. You may need to have a basic understanding of popular regression models like linear & logistic as the course doesn't cover mathematical aspects in detail

2020年10月5日

The course is informative & well taught. I would have liked to spend more time on GLM models, such as logistic regression. The Swirl assignments seem a bit outdated method of learning code and a bit of a hassle.

2020年7月23日

Content is excellent and in depth. Structure could be better to present materials in a more organized fashion, particularly on how all the concepts and tools relate, and complex results interpretation.

2018年2月20日

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.

2019年5月4日

Very good course. Though basic, it provides you with the first tools and knowledge. The forums aren't what they used to be it seems, but you can find almost any answer there from past courses.

2018年4月5日

Very good at presenting basic concepts. I highly reccomend saving the quiz questions as a good guide as to what you should know. I wish there were more material on generalized linear models.

2016年12月10日

I was hoping to learn about PROBIT models. I know they are very similar to LOGIT ones, but still... the pace is a little bit too fast and I think it requires more time than what it says.

2016年2月10日

This was a tough class covering a lot of material. The last week on logistic regression completely lost me. If you're new to stats like me you might want to take it more than once.

2019年3月22日

Really Fun Course. There is a lot to learn in this topic and this could be studied for a lifetime. I feel like I could apply this to discover solutions for issues at work.

2018年4月20日

Good course, worth taking. It points out the importance of looking deeper into the world of regression models and creates right mindset and anchors for future development.

2018年5月26日

I appreciate coefficients interpretation and variance influence to choose among models.

Running code takes a few seconds, understanding the model's outputs is a much hard

2019年2月19日

Probably the most conceptually challenging and practically useful course in the JH data science certification series (so far... I have a few more courses to complete).

2017年9月29日

This time the professor Brian Caffo was more helpfull, explained better the concepts, and sometimes repeated some of the most important information... Good course!

2017年12月1日

Good course for basic regression. Would have enjoyed more time spent on properly interpreting results and how they are relevant to answering business questions.

2018年9月10日

Nice course that helps make your foundations in regression modelling strong. The complexity of the course project can be increased to a more difficult level.

2018年6月29日

This course is a practical introduction to the regression models. Materials and organization are great, however slides and presentations require some work.

2016年8月19日

Good course. My only negative remark is that I really missed the swirl exercises that were available for the other courses of this specialization.

2016年10月24日

Great course to learn various regression models and "R" tools to implement them efficiently, but

was little hard to keep with the deadline.