We may earn an affiliate commission when you visit our partners.

Statistical Methods and Data Analysis

For statistical methods, the course focuses on understanding and application of different concepts and tools of statistics. You will be introduced to data visualization, which is an indispensable tool in this period of vast information around us. In this course, you will learn how to summarize data using descriptive statistics. Next, you will learn about sampling and how to make inferences about the population from a sample via probability theory. You will understand the difference between experimental and observational data. You will learn how to analyze experimental data using tests of significance. For observational data, you will learn correlation analysis and regression analysis. Finally, the course will help you to learn about regression with big data.

For programming skills, you will learn R as a programming language for statistical computing. R is a free software environment for statistical computing and has lots of support information available on the Internet. At the end of this course, you will have the confidence of executing your research project using R.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Two deals to help you save

Save money when you learn. Here are two deals and offers that may be relevant to this course.

All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until December 2

Annual Subscription

Invest in your career growth and save. Start your annual subscription to Coursera Plus and access 10,000+ programs.

Valid until March 12, 2027

Save 40% Off 3 Months

Access thousands of top-rated learning programs with a Coursera Plus monthly subscription and take 40% off 3 months for a limited time.

What's inside

Syllabus

Data Visualization

Statistical methods, by definition, are tools for identifying patterns in large datasets. This module takes the first step towards statistical analysis by exploring various strategies for visualizing data, an increasingly important skill in today’s era of big data. This module explains the different forms of data, types of plots, and charts used to depict the different forms of data. In addition, the module focuses on different visualization techniques appropriate for big data.

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.

Save

Career center

Learners who complete Statistical Methods and Data Analysis will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Statistical Methods and Data Analysis .

The Oxford Handbook of Public Policy

Save

This handbook provides a comprehensive overview of the field of public policy, with chapters on a wide range of topics, from theoretical foundations to specific policy areas.

Statistical Methods and Data Analysis

Two deals to help you save

What's inside

Syllabus

Save this course

Career center

Reading list

Share

Similar courses

Coursera Buyer Protection & Guarantee

7-Day Free Trial & Free Audit

14-Day Refund Guarantee

Verified Academic & Industry Partner