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Вернуться к Logistic Regression in R for Public Health

Отзывы учащихся о курсе Logistic Regression in R for Public Health от партнера Имперский колледж Лондона

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Оценки: 318

О курсе

Welcome to Logistic Regression in R for Public Health! Why logistic regression for public health rather than just logistic regression? Well, there are some particular considerations for every data set, and public health data sets have particular features that need special attention. In a word, they're messy. Like the others in the series, this is a hands-on course, giving you plenty of practice with R on real-life, messy data, with predicting who has diabetes from a set of patient characteristics as the worked example for this course. Additionally, the interpretation of the outputs from the regression model can differ depending on the perspective that you take, and public health doesn’t just take the perspective of an individual patient but must also consider the population angle. That said, much of what is covered in this course is true for logistic regression when applied to any data set, so you will be able to apply the principles of this course to logistic regression more broadly too. By the end of this course, you will be able to: Explain when it is valid to use logistic regression Define odds and odds ratios Run simple and multiple logistic regression analysis in R and interpret the output Evaluate the model assumptions for multiple logistic regression in R Describe and compare some common ways to choose a multiple regression model This course builds on skills such as hypothesis testing, p values, and how to use R, which are covered in the first two courses of the Statistics for Public Health specialisation. If you are unfamiliar with these skills, we suggest you review Statistical Thinking for Public Health and Linear Regression for Public Health before beginning this course. If you are already familiar with these skills, we are confident that you will enjoy furthering your knowledge and skills in Statistics for Public Health: Logistic Regression for Public Health. We hope you enjoy the course!...

Лучшие рецензии

RP

18 дек. 2020 г.

Very good specialisation on logistic regression, with depth info not only on how-to of the model creation itself, but interpreting and choosing between multiple ones. I fully recommend it.

RR

23 дек. 2020 г.

This is a wonderful course. Anyone who wants to model a binary classification model must go for this course. It covers everything in details with logic and humour.

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26–50 из 65 отзывов о курсе Logistic Regression in R for Public Health

автор: Cecil C L

25 янв. 2022 г.

The course needs more exercises to practice R! Good Professors! Clear and Friendly expositions, thanks a lot!

автор: Sara A

30 мар. 2020 г.

Very valuable information presented in a very clear way. It was super useful to me. Thanks!

автор: Pau G

3 мар. 2020 г.

A good overview of Logistic Regression from zero.

A very useful tool for public health data

автор: Moses C B A

1 апр. 2019 г.

This is one of the best courses. Dr. Alex is amazing and delivers the content quite well.

автор: Dwayne R T

25 янв. 2021 г.

The material is comprehensive and the lecturer is amazing at explaining principles.

автор: Fidel G

19 янв. 2020 г.

Awesome course and looking forwards to dive into more Statistical analysis

автор: Arnt D

20 июля 2020 г.

Excellent course. To the point explanations with a good sense of humour.

автор: yi j

1 февр. 2020 г.

Very practical and explicit course about logistic regression.

автор: Adriana R V

19 нояб. 2020 г.

Excellent, great teacher and very clear code instructions.

автор: Joseph L

28 авг. 2020 г.

Good, easy to follow introduction to logistic regression

автор: M. A S

11 апр. 2021 г.

Excellent course. Prof Bottle is great.

Thanks

автор: Dhan K B

19 окт. 2020 г.

I learned regression in R through this course

автор: Khan S I

15 мар. 2021 г.

The course was worth the time and efforts.

автор: Victor I M

24 сент. 2020 г.

Excellent demonstrations and explanations.

автор: Shek L T

15 мая 2020 г.

Excellent teaching! very useful R codes!

автор: Enrique L

27 мар. 2020 г.

Really good course!! Highly recommended.

автор: qianmengxiao

14 апр. 2020 г.

I like this course!The prof is good

автор: Shova P

15 июля 2019 г.

Course is very easy to follow

автор: Don E

31 июля 2020 г.

AWESOME. Very organized.

автор: Jin C

15 июля 2020 г.

Thank you

You are the best!

автор: Ning D

27 июля 2019 г.

very recommendable course

автор: JOEL C H M

2 авг. 2020 г.

It was so useful

автор: fabien M

19 апр. 2020 г.

Very interesting

автор: Yasna P S

4 мар. 2020 г.

Excellent course

автор: Martina

27 июля 2021 г.

Amazing course!