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.
Status: Regression Analysis
Regression Analysis
Status: Correlation Analysis
Correlation Analysis
Intermediate·Course·15 hours
Featured reviews
5.0
·Reviewed Sep 11, 2023
This is is an excellent course! Thank you for providing it to us online, and please, I look forward to have access to more advance courses on statistical analysis for public health from ICL!
5.0
·Reviewed Apr 3, 2020
This is an excellent course to learn how to think statistically with respect to linear regression. The course covers a lot of materials and equips one to further explore this vast area.
5.0
·Reviewed Feb 27, 2021
The course was an excellent utilisation of time. I am looking forward to explore further and utilise the skills I acquired.
5.0
·Reviewed May 17, 2023
Excellent course, well taught, well-paced. I feel more confident in using R for regression analysis.
5.0
·Reviewed Jan 14, 2023
I learned so much - definitely met learning objectives in terms of statistics and use of R for regression modeling!
5.0
·Reviewed Aug 16, 2020
Excellent online course with plenty of learning to now take away and apply to other datasets to enhance this learning.
4.0
·Reviewed Jan 18, 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!
4.0
·Reviewed Jun 7, 2020
Excellent course! I liked the guided activities however there were some do-it-yourself activities that were required before learning of the necessary code.
5.0
·Reviewed Dec 8, 2020
Wonderful course. Anyone with any background can attend this course. The general idea of regression you will get from here can be applied in any academic domain.
5.0
·Reviewed Nov 28, 2021
This is the best course to get started with linear regression and R as the instructor explains step by step on each strategy
5.0
·Reviewed Aug 26, 2019
Great Course. For a person wanting to learn coding from scratch it is very friendly and easy to understand.
5.0
·Reviewed Apr 29, 2020
Thorough explanation of linear regression, building on the basics right up to model building. Highly recommend! :)
All reviews
Showing: 20 of 112
All Learners
All Stars
Most Helpful
R
Rahul
5.0
·Reviewed Dec 9, 2020
Wonderful course. Anyone with any background can attend this course. The general idea of regression you will get from here can be applied in any academic domain.
W
William
5.0
·Reviewed 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
R
Rashidul
5.0
·Reviewed 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.
M
Mohammad
5.0
·Reviewed Oct 4, 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
F
Fasiha
5.0
·Reviewed May 28, 2023
With no prior background in programming and computational analysis, I have found this course as best starter to gain fundamental skills that will help me excel in my current field of life sciences. This course will surely help me in writing meta-analysis and doing statistical analysis of my research projects with a little bit guidance from statisticians rather than relying on statisticians to do data analysis part of my research design. Thanks Imperial College London, the instructors and Coursera to bring this brilliant specialization to me.
H
Hector
5.0
·Reviewed Sep 18, 2020
This is one of the best courses I have ever taken. Congratulations to the design team and the instructors. The level of this course is excellent and the feedback the instructor provided helped me to go further. I am so happy I took this course.
R
Rashmi
5.0
·Reviewed Sep 22, 2019
Excellent course. We get a lot of hands on training in building regression models and crystal clear concepts.
S
Sergio
5.0
·Reviewed Sep 20, 2019
Excellent course, with great classes and a large data set for you to test your computational skills.
V
Vivekananda
5.0
·Reviewed Jun 21, 2019
Perhaps, the best linear regression course available online! Great job!
L
L
2.0
·Reviewed Feb 17, 2021
Reading materials and practicals are a bit messy. Poorly formatted, lack
of logical structure, and low res screenshots of code and R console outputs
(some of which code is buggy). Please provide the code that we can
actually run, as R or Rmd files. Lack of quality unfortunately is not to professional or academic
standard, you would be expected to produce a lot better on the job or for assignments so
it's not a good example to set here. I hope the course content for on campus students is better than this. I imagine it is, so it just goes to show this was thrown together without any real care or quality control.
V
Vassilena
5.0
·Reviewed Aug 8, 2022
This was a great course! I have been stuck on the analysis of my research data and was looking for some kind of course which can help me develop an intuition how to build models, what makes sense clinically and statistically. This course exceeded my expectations. It provides short videos, helpful readings as well as exercises to implement the presented concepts. It helped me develop a structure how to approach the analysis of a data set and what is the good practice in selecting variables and building your model! The course was not only very informative but also very enjoyable.
A
Aedrian
5.0
·Reviewed Jan 22, 2021
As my first formal foray to R, I highly appreciate the hands-on approach of this course. While I have been aware and using linear regression for various research endeavors prior to this course, the material has provided me a more technical perspective on the advantages, assumptions and limitations of this statistical technique. It is extremely difficult to get decent scores in the quiz without actually trying R, so be prepared to devote more time and effort than you normally would in a MOOC.
J
John
5.0
·Reviewed Jul 17, 2023
I really enjoyed this course, which broke down the steps of how to build a multivariable regression model, from examining individual data, exploring its correlations, fitting a linear regression model, coding all of these in R, and even provided tips on how to put all of these together in a research paper. I don't have any delusions of being a data analyst after taking this course, but it gives me the confidence to take on a project and do a decent job of it.
B
Brenda
5.0
·Reviewed Jul 2, 2020
I loved the step-by-step approach and learned a lot in this course! I only wish that activities could be assessed (perhaps by peer review, as I have seen in other courses), so I could know if I am on the right track, or how to troubleshoot certain issues (still struggling with interaction terms...). Otherwise, definitely a great course with great materials teaching very useful skills :)
A
Alireza
5.0
·Reviewed May 26, 2022
fantastic!
unlike the previous course from the same specialization which was a little bit fundamental, this course was so comprehensive that everyone can easily learn from basics to advanced levels of regression, along with all mistakes scientists may make when doing a regression
thank you so much for the course
K
kalyango
5.0
·Reviewed 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.
S
Sandro
5.0
·Reviewed Sep 24, 2020
Interesting and well planned. It follows the path laid down in the previous course, alternating short videos and moments of personal reading and reflection, followed by feedbacks. Plus the chance to see some real data processing, both guided and do-it-yourself. Good!
T
Tommy
5.0
·Reviewed 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.
S
Swetha
5.0
·Reviewed May 19, 2020
The course explained the intricacies of Linear Regression very well. esp. the interaction effect and addressing categorial variables and how to select variables, which is often overseen in most content/ courses. Excellent course!
S
Sabine
5.0
·Reviewed 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.