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Learner Reviews & Feedback for Introduction to Statistics & Data Analysis in Public Health by Imperial College London

4.7
stars
1,473 ratings

About the Course

Welcome to Introduction to Statistics & Data Analysis in Public Health! This course will teach you the core building blocks of statistical analysis - types of variables, common distributions, hypothesis testing - but, more than that, it will enable you to take a data set you've never seen before, describe its keys features, get to know its strengths and quirks, run some vital basic analyses and then formulate and test hypotheses based on means and proportions. You'll then have a solid grounding to move on to more sophisticated analysis and take the other courses in the series. You'll learn the popular, flexible and completely free software R, used by statistics and machine learning practitioners everywhere. It's hands-on, so you'll first learn about how to phrase a testable hypothesis via examples of medical research as reported by the media. Then you'll work through a data set on fruit and vegetable eating habits: data that are realistically messy, because that's what public health data sets are like in reality. There will be mini-quizzes with feedback along the way to check your understanding. The course will sharpen your ability to think critically and not take things for granted: in this age of uncontrolled algorithms and fake news, these skills are more important than ever. Prerequisites Some formulae are given to aid understanding, but this is not one of those courses where you need a mathematics degree to follow it. You will need only basic numeracy (for example, we will not use calculus) and familiarity with graphical and tabular ways of presenting results. No knowledge of R or programming is assumed....

Top reviews

SK

Oct 11, 2019

This is the best course among all I've taken..

The instructor has presented the content precisely.

I highly recommend to those who are looking to explore R in the field of health

LA

May 25, 2019

Was a very nicely done and clear course to build or re-build foundation for most common statistical concepts and an intro to using R via R-Studio for your work with them on the basics.

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151 - 175 of 285 Reviews for Introduction to Statistics & Data Analysis in Public Health

By Marcos d S M

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Nov 20, 2021

Good introduction to Data Analysis in Public Health

By Muhammad A

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Mar 31, 2021

A great course with a lot of examples for practicing

By Alia G

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Sep 14, 2020

Хорошие основы, многое сложилось в цельную картинку

By JIANG J

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Oct 26, 2020

A truly excellent R course for beginners like me!

By Nathiya N

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Jun 6, 2020

I found the course really interesting and useful.

By bouopda k y

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Sep 30, 2020

très interessant comme cours pour devenir expert

By Marzhan N

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Sep 9, 2020

Thank you for the interesting and useful course!

By alexa v

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Aug 3, 2022

this course was interesting and easy to learn

By Adegorite O D

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Jul 29, 2020

Awesome course for anyone that is interested

By Norberto I T

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Aug 16, 2020

The abililty to use R is very,very useful.

By Nacho O

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Dec 7, 2019

A great introduction, it's worth the time.

By Oriolowo T A

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Jun 14, 2019

Awesome course and the teaching was superb

By salome a

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May 10, 2019

Excellent introduction to statistics and R

By Anderson S

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Apr 27, 2019

I love the simplicity of the explanations

By Zaithwa M

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Apr 25, 2023

Excellent course with an excellent tutor

By Dhan K B

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Aug 15, 2020

Good course to get into Health analytics

By Rizky M

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Aug 1, 2019

Very helpful, and interesting lecturer !

By Negli R G A

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Sep 30, 2022

Eu gostei e aprendi muito com o curso.

By Tanawin N

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Sep 2, 2019

Great experience through great efforts!

By AmanySamirMohamed A

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Oct 30, 2021

more helpful and add new skills to me

By Yan M

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Jan 4, 2021

Very clear! Highly recommend this one!

By AGGREY G O

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Jul 16, 2020

Highly educative with relevant content

By Thomas J H

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Mar 31, 2019

Clear and no nonsense. Do recommend.

By Shaibu I

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Apr 8, 2020

Fantastic course and lecturer, kudos

By José Á J R

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Aug 5, 2024

Very useful introduction to RStudio