Chevron Left
Retour à Linear Regression in R for Public Health

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

449 évaluations

À propos du cours

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....

Meilleurs avis


3 avr. 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.


1 févr. 2021

This was a wonderful course, for many reasons, the best of which was I felt as if I was finally getting into a real-world data analysis situation. I recommend it highly.

Filtrer par :

76 - 95 sur 95 Avis pour Linear Regression in R for Public Health

par Anderson S

7 juin 2019

Excellent course

par Juan C M G

19 mars 2021

Great course!

par Yasna P S

4 mars 2020

Good course

par hippo d

8 mai 2021

Thank you.

par Jeshua R G

6 mars 2020


par Henrique A

13 avr. 2019


par Tiar S F

15 mai 2021

it's fun

par Shakil A S

16 févr. 2021


par Abdessamad B

7 mai 2020



25 juil. 2020


par Eleftheria K

24 avr. 2020

The instructor was wonderful. Both the videos and the exercises were very hepful for understanding linear regression. The feedback was also incredibly valuable and helped us understand possible mistakes. I didn't rate the course with four stars because of some mistakes in the videos (for example when we discuss interaction the formula with the interaction term appears both in the beginning and afterwards) as well as in a question in the final test. They might seem like details but for a beginner it causes a bit of confusion and an unnecessary loss of time. Other than that, the course is very good.

par Pippa D

9 sept. 2020

Helpful and engaging. I did have to occasionally seek extra explanations elsewhere to supplement what is covered in the course - eg it doesn't explain all the information given in the R results for a linear regression. But well worth doing.

par Vijay B

19 janv. 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!

par Rupok C

20 juin 2020

Nice course for the beginner who is pursuing health research and its multivariate analysis. It would be better if it is provided more elaborately in video lectures.

par Julie N

8 juin 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.

par Saint L

21 avr. 2020

Thanks to all the staff at ICL.

par Eri T

11 déc. 2021

Too easy

par Albert N

19 nov. 2021

I e is

par Harini K

22 oct. 2020

The feedback and explanations within the course are not as good for this one versus the feedback in the first course of the specialization. Additionally, the example used for the course should be better explained before usage of the model repeatedly in the course. Oh and some of the code has errors in this course and the final class code is not great in this one. It doesn't help me understand the errors when I go back for feedback/assistance. Being an online course with limited interaction, waiting for someone to respond to a question in the forum requires too much time.

par Jean-Philippe M

1 janv. 2021

Overall the course was interesting and informative. i whished that more practical exercises (or labs) in r would have been provided.