Course Features
Duration
3 weeks
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Effort
6 hours per week
Teaching Type
Self Paced
Course Description
Course Overview
International Faculty
Post Course Interactions
Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
As such we expect that you are already familiar with some basic topics in statistics.
Some basic calculus will be used, along with some aspects of probability theory: computation of expectation and variance of a random variable with known PDF, the central limit theorem, Bayes’ theorem
Prior knowledge of all the material covered
What You Will Learn
Apply certain procedures (resampling, bootstrapping, non-parametric approach) when confronted with non-standard situations.
Construct and interpret confidence intervals, learn how to perform hypothesis testing in various settings, and know how these two concepts are related.
Make and interpret numerical and graphical summaries of datasets.
Perform simple and multiple linear regression on quantitative and categorical variables.
Use the R software package to perform all these tasks.
Use various techniques to find estimators for unknown parameters and how to compare them.
Course Instructors