This Introduction to Statistics and Data Analysis in Public Health offered by Coursera in partnership with Imperial College London 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.
Get more detailsVisit official programme website
- Introduction to Statistics in Public Health
- Types of Variables, Common Distributions and Sampling
- Introduction to R and RStudio
- Hypothesis Testing in R
More Details on Coursera Plus:
- Learn Anything: Explore any interest or trending topic, take prerequisites, and advance your skills
- Save money: Spend less money on your learning if you plan to take multiple courses this year
- Flexible Learning: Learn at your own pace, move between multiple courses, or switch to a different course
- Unlimited Certificates: Earn a certificate for every learning program that you complete at no additional cost
Check out the full curriculumVisit official programme website
- 1 months
Start dates & application deadlines
DisciplinesPublic Health Statistics Machine Learning View 51 other Short Courses in Statistics in United States
Explore more key informationVisit official programme website
We are not aware of any academic requirements for this programme.
We are not aware of any English requirements for this programme.
- You will only need an interest in analysing quantitative data and familiarity with reading standard graphs and tables of data.
- 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.
Make sure you meet all requirementsVisit official programme website
InternationalFreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
NationalFreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access.
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
Double-check all feesVisit official programme website
Apply and win up to €10000 to cover your tuition fees.