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學生對 伦敦帝国学院 提供的 Linear Regression in R for Public Health 的評價和反饋

4.8
58 個評分
10 個審閱

課程概述

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....

熱門審閱

VD

Jun 21, 2019

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

RH

May 22, 2019

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

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1 - Linear Regression in R for Public Health 的 10 個評論(共 10 個)

創建者 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

創建者 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.

創建者 Henrique A d S

Apr 13, 2019

Excelente

創建者 Thomas J H

Mar 31, 2019

Excellent. Clear, succinct. Good examples.

創建者 Enrique D O

May 20, 2019

HIghly recommended

創建者 Rahim H

May 22, 2019

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

創建者 Anderson S

Jun 07, 2019

Excellent course

創建者 Vivekananda D

Jun 21, 2019

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

創建者 Nimmi P

Jul 30, 2019

good one for model building in any stream

創建者 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.