- R Programming
- Linear Regression
- Statistical Hypothesis Testing
- Linear Algebra
- Confidence Interval
Advanced Statistics for Data Science Specialization
Familiarize yourself with fundamental concepts in probability and statistics, data analysis and linear models for Data Science.
What you will learn
Learn about probability, expectations, conditional probabilities, distributions, confidence intervals, bootstrapping, binomial proportions, and more.
Understand the matrix algebra of linear regression models.
Learn about canonical examples of linear models to relate them to techniques that you may already be using.
Skills you will gain
About this Specialization
Applied Learning Project
The Advanced Statistics for Data Science Specialization incorporates a series of rigorous graded quizzes to test the understanding of key concepts such as probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling.
How the Specialization Works
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
There are 4 Courses in this Specialization
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