Endorsed by
Coursera 4.3 (9)
Overview
This Introduction to Statistics and Data Analysis in Public Health course 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.
What you will learn
- Defend the critical role of statistics in modern public health research and practice
- Describe a data set from scratch, including data item features and data quality issues, using descriptive statistics and graphical methods in R
- Select and apply appropriate methods to formulate and examine statistical associations between variables within a data set in R
- Interpret the output from your analysis and appraise the role of chance and bias
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Statistics in Public Health
- Types of Variables, Common Distributions and Sampling
- R and RStudio
- Hypothesis Testing in R
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Disciplines
Public Health Statistics Data Science & Big Data View 106 other Short Courses in Public Health in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Beginner Level
- You will only need an interest in analysing quantitative data and familiarity with reading standard graphs and tables of data.
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.
Make sure you meet all requirements
Visit programme websiteTuition Fee
To always see correct tuition fees
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
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.
Funding
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.
Improve page content