Linear Regression in R for Public Health に戻る

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Welcome to Linear Regression in R for Public Health!
Public Health has been defined as “the art and science of preventing disease, prolonging life and promoting health through the organized efforts of society”. Knowing what causes disease and what makes it worse are clearly vital parts of this. This requires the development of statistical models that describe how patient and environmental factors affect our chances of getting ill. This course will show you how to create such models from scratch, beginning with introducing you to the concept of correlation and linear regression before walking you through importing and examining your data, and then showing you how to fit models. Using the example of respiratory disease, these models will describe how patient and other factors affect outcomes such as lung function.
Linear regression is one of a family of regression models, and the other courses in this series will cover two further members. Regression models have many things in common with each other, though the mathematical details differ.
This course will show you how to prepare the data, assess how well the model fits the data, and test its underlying assumptions – vital tasks with any type of regression.
You will use the free and versatile software package R, used by statisticians and data scientists in academia, governments and industry worldwide....

Oct 04, 2019

The course was really great. The instructor explained the things in a lucid manner. Also the reading materials were great. Thank you so much for this course

Dec 23, 2019

Great course that takes you step by step on how to create model selection in R which you can be apply into the real world.

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by William E

•Jul 12, 2019

This course is excellent- if you want a solid understanding of the basics, this is as good as it gets. I would say it is most suited for somebody who wants a more conceptual rather than mathematical understanding of the subject, but its still has a good balance between the both approaches. The videos are very well presented, the lecturer is very professional and has clear and engaging style [not like most stats teachers ;) ]. My only difficulty was that I am already quite an experienced R user and the coding methods were quite different to my style, that's not a criticism really as there are numerous ways to remove the outer layer of a feline, as they say. There a decent number of typos and I was a little frustrated with some of the answers to the questions being wrong (I was convinced on a couple of occasions that I had it right and they didn't). I'm not the expert so they were almost certainly right it's just the explanation to the answer didn't really help me understand. Also for extra browny points it would great if the R code was formatted in a codey way in the reading lesson- like in stackoverflow. It kind of gets lost in the text. In summary if you are reading this chances are you want to know whether or not to do this course. DO IT The end

by Rashidul H

•May 30, 2019

An excellent Coursera content provided from such a renowned faculty with so much organized and systematic instructions. I truly enjoyed the whole course to learn the concept and had ample opportunity with tasks to practice analysis skills with the provided example data. I would really recommend anyone to participate on this course. Best wishes to Imperial faculty for offering such a great course.

by Rashmi M

•Sep 22, 2019

Excellent course. We get a lot of hands on training in building regression models and crystal clear concepts.

by Sergio P

•Sep 20, 2019

Excellent course, with great classes and a large data set for you to test your computational skills.

by Kalyango E

•Dec 21, 2019

Initially I was scared of R programming and statistics because i thought it was for data scientists, but this course was easy to follow and the exercises are rigorous. You come out of this course confident in your analytic skills. Wonderful teachers and thanks for sharing your knowledge.

by Tommys J G G

•Aug 15, 2019

Excellent course! Very hard in some aspects but very engaging and it provides students with deep knowledge of linear regression, epidemiology with R usage, and biostatistics skills which I consider essential for every Public Health Practitioner today.

by Sabine f

•Dec 10, 2019

In a matter of days I was able to understand linear regression using R. Great videos and homework assignments that are doable and can be applied directly to own research. This course is a must for any Phd student in healthcare.

by MOHAMMAD R W

•Oct 04, 2019

The course was really great. The instructor explained the things in a lucid manner. Also the reading materials were great. Thank you so much for this course

by Fidel G

•Dec 23, 2019

Great course that takes you step by step on how to create model selection in R which you can be apply into the real world.

by Rodolfo I C S

•Aug 27, 2019

Great Course. For a person wanting to learn coding from scratch it is very friendly and easy to understand.

by Jose L V V

•Jan 27, 2020

good explanations about the utilities of simple and multiple linear regression in public health!!!

by Pau G C

•Feb 24, 2020

Good course to get familyar with linear regression from the very begining , Very useful lectures

by Vivekananda D

•Jun 21, 2019

Perhaps, the best linear regression course available online! Great job!

by yi j

•Feb 02, 2020

Very practical and explicit course about linear regression.

by Rahim H

•May 22, 2019

Amazing course, it has been great revision for me with OLS

by Seungyeon J

•Jan 11, 2020

I highly recommend this course. The lecture is so good.

by Thomas J H

•Mar 31, 2019

Excellent. Clear, succinct. Good examples.

by Nimmi P

•Jul 30, 2019

good one for model building in any stream

by neil p

•Jan 07, 2020

Charming and really fun at 2x

by Enrique D O

•May 20, 2019

HIghly recommended

by Darija K

•Feb 05, 2020

Excellent course.

by Anderson S

•Jun 07, 2019

Excellent course

by Henrique A d S

•Apr 13, 2019

Excelente

by Vijay B S

•Jan 19, 2020

Great way to start modelling using R. Course instructor is good. The concepts are well introduced and put into practice with R. Finally, to get a hang of the whole thing, you need a lot of practice!