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Statistics Fundamentals in R

Updated 03/2026
Discover the power of statistics in R. Learn the key statistical concepts, topics, and techniques used by data scientists and statisticians every day.
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Track Description

Statistics Fundamentals in R

Statistics is the study of how best to collect, analyze, and draw conclusions from data. A strong foundation will serve you well, no matter what industry you work in. In this beginner’s track, you'll learn the concepts, topics, and techniques used by data scientists and statisticians every day—including observational studies and experiments, correlation, regression, exploratory data analysis, and inference. You’ll also develop your stats skills by working with real-world data, including Stack Overflow surveys, real estate prices, and medical shipment data. Start this track today to learn about the power of statistics and how it can be used in your day-to-day analyses!

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Statistics in R

    Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

  • Course

    2

    Introduction to Regression in R

    Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

  • Course

    4

    Sampling in R

    Master sampling to get more accurate statistics with less data.

  • Course

    5

    Hypothesis Testing in R

    Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

  • Project

    bonus

    Hypothesis Testing with Men's and Women's Soccer Matches

    Perform a hypothesis test to determine if more goals are scored in women's soccer matches than men's!

Statistics Fundamentals in R
5 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, this track is designed for beginners who are interested in learning statistics and its various applications.

What is the programming language of this Track?

The programming language used in this track is R, which is widely used by data scientists and statisticians for statistical analysis.

Which jobs will benefit from this Track?

This track will benefit professionals in a variety of fields such as data science, statistics, business, finance, healthcare, and many others.

How will this Track prepare me for my career?

This track will provide you with a strong foundation in statistics and data analysis, which are highly sought-after skills in many industries. It will also give you hands-on experience working with real-world data.

How long does it take to complete this Track?

The track is self-paced, so it depends on how much time you can devote to it. Typically, it takes around 20 hours to complete as it consists of several courses.

What's the difference between a skill track and a career track?

A skill track is designed to upskill users in a specific set of skills, while a career track is focused on preparing users for a specific job or career path.

Can I switch between courses within this Track?

Yes, you can switch between courses within this track based on your interests and learning goals.

Are the datasets provided in this Track created from real-world examples?

Yes, the datasets provided in this track are created from real-world examples to give you practical experience in data analysis.

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