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Avis et commentaires pour d'étudiants pour Logistic Regression in R for Public Health par Imperial College London

4.8
étoiles
304 évaluations
63 avis

À propos du cours

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!...

Meilleurs avis

RP
18 déc. 2020

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 déc. 2020

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 sur 62 Avis pour Logistic Regression in R for Public Health

par Moses C B A

1 avr. 2019

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

par Dwayne R T

25 janv. 2021

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

par Fidel G

19 janv. 2020

Awesome course and looking forwards to dive into more Statistical analysis

par Arnt D

20 juil. 2020

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

par yi j

1 févr. 2020

Very practical and explicit course about logistic regression.

par Adriana R V

19 nov. 2020

Excellent, great teacher and very clear code instructions.

par Joseph L

28 août 2020

Good, easy to follow introduction to logistic regression

par M. A S

11 avr. 2021

Excellent course. Prof Bottle is great.

Thanks

par Dhan K B

19 oct. 2020

I learned regression in R through this course

par Sumaiya I

15 mars 2021

The course was worth the time and efforts.

par Victor I M

24 sept. 2020

Excellent demonstrations and explanations.

par Shek L T

15 mai 2020

Excellent teaching! very useful R codes!

par Enrique L

27 mars 2020

Really good course!! Highly recommended.

par qianmengxiao

14 avr. 2020

I like this course!The prof is good

par Shova P

15 juil. 2019

Course is very easy to follow

par Don E

31 juil. 2020

AWESOME. Very organized.

par Jin C

15 juil. 2020

Thank you

You are the best!

par Ning D

27 juil. 2019

very recommendable course

par JOEL C H M

2 août 2020

It was so useful

par fabien M

19 avr. 2020

Very interesting

par Yasna P S

4 mars 2020

Excellent course

par Martina

27 juil. 2021

Amazing course!

par TANG

30 oct. 2019

Very helpful!

par Majeda m

17 nov. 2021

very good

par Shakil A S

17 févr. 2021

Amazing!