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Voltar para Modelos Regressivos

Comentários e feedback de alunos de Modelos Regressivos da instituição Universidade Johns Hopkins

4.4
estrelas
3,203 classificações
540 avaliações

Sobre o curso

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....

Melhores avaliações

KA
16 de Dez de 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.

BA
31 de Jan de 2017

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.

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451 — 475 de 520 Avaliações para o Modelos Regressivos

por Raul M

16 de Jan de 2019

This course should be targeted for Data Scientists, in my opinion it is more for statisticians.

Too much about the insight of statistics and some but not enough about how to use the statistic tools.

por benjamin s

20 de Jun de 2018

A good (although slightly frustrating) course, attempted once but had to come back after studying the material in class, quite a heavy course if you've not been taught regression before

por Guilherme B D J

21 de Ago de 2016

Given the importance of this subject, this course should have been split in two or more or have a longer duration to properly address subjects as GLM or model selection techniques.

por Marco A M A

9 de Mai de 2016

This course is better than Statistical Inference, and I think it is as useful. Non credit excersise are still very good at helping with understanding in practice what is going on.

por Rok B

28 de Jun de 2019

Useful class, but the content often simple in nature was explained in a confusing/complicated way. But the material is important and there is purchase for taking the class

por Jesse K

2 de Nov de 2018

The material was a little disjointed and not always explained with examples. Passing this course required a significant amount of outside study and research.

por Jason M C

29 de Mar de 2016

This is a decent class, covering linear regression and a few of its variants in good detail. It's a challenging subject, but presented acceptably here.

por Anamaria A

12 de Mar de 2017

Lots of material needs additional study (from different sources) as it's only summarily explained. Much math without the link to the praxis :-(

por Manuel M M

10 de Fev de 2020

The content was exposed in a very confused manner. I did not like how the teacher explained. It seemed more difficult than it really is

por LU Z

26 de Set de 2018

Starting from the first week swirl practice, course content is poorly organized making even simple concept difficult to understand.

por Hendrik F

17 de Jan de 2016

I find it very tough to understand everything. Buying the course book helps to overcome this. You have to dedicate a lot of time.

por Mark S

24 de Abr de 2018

Lots of math, but it would be more productive to focus more on the output of R and better understand the results

por Mertz

20 de Mar de 2018

Bad audio and video quality. Too fast on some complex ideas and too slow when come repetitions between videos...

por Andres C S

1 de Mar de 2016

I think this course needs more emphasis on practical applications and less mathematical background.

por Erwin V

20 de Dez de 2016

Very interesting course, yet course content could be spread more evenly (week 4 is really a lot)

por Prabeeti B

17 de Set de 2019

Course has more theoretical concept than application.. It has to be more application based

por Praveen J

22 de Abr de 2020

I think a revamping of the concepts in a more ellabroate way is required in the course

por Suleman W

9 de Nov de 2017

I did find it difficult to follow and understand some of the materials.

por Rafal K

28 de Fev de 2017

Many things are not clear enough in multivariable regression part.

por Eric L

2 de Fev de 2016

good quick overview, could have more actual R examples in lectures

por Ansh T

22 de Mar de 2020

Topics like logistic regression were not explained clearly

por Angela W

27 de Nov de 2017

I learned a lot, but it was so much content for 4 weeks!

por Gareth S

16 de Jul de 2017

Expects a level of statistical knowledge already.

por David S

4 de Nov de 2018

needed to consult external resources extensively

por Lei M

23 de Ago de 2017

Some of the materials are too much math for me.