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Bewertung und Feedback des Lernenden für Logistic Regression in R for Public Health von Imperial College London

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315 Bewertungen
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65 Bewertungen

Über den Kurs

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!...

Top-Bewertungen

RP

18. Dez. 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. Dez. 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 von 64 Bewertungen für Logistic Regression in R for Public Health

von Sara A

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30. März 2020

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

von Pau G

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3. März 2020

A good overview of Logistic Regression from zero.

A very useful tool for public health data

von Moses C B A

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1. Apr. 2019

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

von Dwayne R T

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25. Jan. 2021

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

von Fidel G

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19. Jan. 2020

Awesome course and looking forwards to dive into more Statistical analysis

von Arnt D

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20. Juli 2020

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

von yi j

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1. Feb. 2020

Very practical and explicit course about logistic regression.

von Adriana R V

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19. Nov. 2020

Excellent, great teacher and very clear code instructions.

von Joseph L

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28. Aug. 2020

Good, easy to follow introduction to logistic regression

von M. A S

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11. Apr. 2021

Excellent course. Prof Bottle is great.

Thanks

von Dhan K B

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19. Okt. 2020

I learned regression in R through this course

von Sumaiya I

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15. März 2021

The course was worth the time and efforts.

von Victor I M

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24. Sep. 2020

Excellent demonstrations and explanations.

von Shek L T

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15. Mai 2020

Excellent teaching! very useful R codes!

von Enrique L

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27. März 2020

Really good course!! Highly recommended.

von qianmengxiao

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14. Apr. 2020

I like this course!The prof is good

von Shova P

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15. Juli 2019

Course is very easy to follow

von Don E

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31. Juli 2020

AWESOME. Very organized.

von Jin C

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15. Juli 2020

Thank you

You are the best!

von Ning D

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27. Juli 2019

very recommendable course

von JOEL C H M

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2. Aug. 2020

It was so useful

von fabien M

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19. Apr. 2020

Very interesting

von Yasna P S

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4. März 2020

Excellent course

von Martina

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27. Juli 2021

Amazing course!

von TANG

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30. Okt. 2019

Very helpful!

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