Introduction to Statistics & Data Analysis in Public Health
Statistical Analysis with R for Public Health,
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.
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| Rating | 4.7★ based on 60 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 2-5 hours/week |
| Starts | Jul 3 (46 weeks ago) |
| Cost | $49 |
| From | Imperial College London via Coursera |
| Instructor | Alex Bottle |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Science Data Science Mathematics |
| Tags | Life Sciences Data Science Probability And Statistics Public Health |
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What people are saying
public health
to statistics in public health.
Excellent course if you want to start using R for public health projects!
I will recommend to all Public Health Practitioners.
Found it pretty basic but would definitely recommend it to anyone just starting out with statistics ? Very practical and explicit course about basic statistics and R. It was fun & easy This is an excellent course, it helps me play a solid foundation about Biostatistics in particular and Public Health in General This course is amazing for candidates looking to gain a fundamental understanding of Public Health Research.
Great way to get introduced to basic concepts of statistical thinking in public health and learning to use R. I expected much more work on R plus barely any of the syntax worked on my Mac.
A MUST HAVE if you want to learn Public Health.
R programming is a excellent tool for analyze data in public health.
the course is very good both in theory and practice with programming in R to public health Aprendí mucho con una metodología bastante didáctica.
Great course to start learning statistics in public health.
I love the example data that are closely related to public health field.
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statistical thinking
I highly recommend it very friendly for new beginners more time needed to reiew R A good introduction to the statistical thinking in order to clarify some basic but esential concepts as: research question, hypothesis, etc Fun, fast paced, applied.
a brief introduction to statistical thinking Overall good!
basic statistics
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 Very easy to understand the basic statistics and know how to use R.Value for money.Many Thanks!!!
reading material
However, there are few lectures (mostly reading material) and many tests are "check yourself" ones.
The course would benefit if current reading material was given in lectures (as it is mostly words) and the more advanced reading material was included with more formal/mathematical description of the concepts.
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| Rating | 4.7★ based on 60 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 2-5 hours/week |
| Starts | Jul 3 (46 weeks ago) |
| Cost | $49 |
| From | Imperial College London via Coursera |
| Instructor | Alex Bottle |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Science Data Science Mathematics |
| Tags | Life Sciences Data Science Probability And Statistics Public Health |
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