We may earn an affiliate commission when you visit our partners.
Course image
Elle O'Brien

How to Describe Data examines the use of data in our everyday lives, giving you the ability to assess the usefulness and relevance of the information you encounter. In this course, learn about uncertainty’s role in measurements and how you can develop a critical eye toward evaluating statistical information in places like headlines, advertisements, and research. You’ll learn the fundamentals of discussing, evaluating, and presenting a wide range of data sets, as well as how data helps us make sense of the world. This is a broad overview of statistics and is designed for those with no previous experience in data analysis. With this course, you’ll be able to spot potentially misleading statistics and better interpret claims about data you encounter in the world. Course assessments focus on your understanding of concepts rather than solving math problems.

Read more

How to Describe Data examines the use of data in our everyday lives, giving you the ability to assess the usefulness and relevance of the information you encounter. In this course, learn about uncertainty’s role in measurements and how you can develop a critical eye toward evaluating statistical information in places like headlines, advertisements, and research. You’ll learn the fundamentals of discussing, evaluating, and presenting a wide range of data sets, as well as how data helps us make sense of the world. This is a broad overview of statistics and is designed for those with no previous experience in data analysis. With this course, you’ll be able to spot potentially misleading statistics and better interpret claims about data you encounter in the world. Course assessments focus on your understanding of concepts rather than solving math problems.

This is the first course in Understanding Data: Navigating Statistics, Science, and AI Specialization, where you’ll gain a core foundation for statistical and data literacy and gain an understanding of the data we encounter in our everyday lives.

Enroll now

Here's a deal for you

Save money when you learn with a deal that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

What's inside

Syllabus

Welcome, Introduction & What Makes a Statistic Useful?
Rethinking Certainty
Talking about Numbers
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Geared for learners without a statistics background, this course strikes a balance between accessibility and comprehensiveness
Taught by Elle O'Brien, who are recognized for their work in statistics education
Serves as a foundation for the Understanding Data: Navigating Statistics, Science, and AI Specialization
Develops critical thinking skills for evaluating statistical information encountered in everyday life
May require a specific interest in data analysis to fully engage with the content
Focuses on understanding concepts rather than solving mathematical problems

Save this course

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

Reviews summary

Broad data literacy for beginners

According to learners, "How to Describe Data" is a largely positive experience, particularly suited for absolute beginners with no prior data analysis experience. Students highly commend its focus on conceptual understanding rather than getting bogged down in complex math. The course is praised for providing clear explanations and well-structured lectures, empowering individuals to critically evaluate statistical information they encounter in everyday life, from news headlines to advertisements. While it serves as a solid foundation for the broader Understanding Data Specialization, some learners with prior statistics knowledge might find the content too basic.
Lectures are well-structured, easy to follow, and concise.
"The lectures are incredibly clear, breaking down complex ideas into manageable pieces."
"The explanations are clear, concise, and highly relevant."
"I've always struggled with statistics, but this course made it accessible and interesting."
Empowers learners to critically assess data in daily life.
"Now I feel much more confident in my ability to interpret news headlines and advertisements that use statistics."
"It truly gives you a critical eye for data in everyday life."
"I can already apply what I've learned to better understand reports at work."
Emphasizes understanding concepts over complex calculations.
"I loved how it focused on understanding concepts rather than getting bogged down in math formulas."
"The course delivered on its promise to teach how to evaluate statistical information without requiring advanced mathematical skills."
"Assessments genuinely test your understanding of the material rather than your math skills."
Perfect for those with no prior data analysis experience.
"This course is exactly what I needed as someone with absolutely no prior data analysis experience."
"As a non-technical professional, this course was perfect for improving my data literacy."
"The course is okay, but quite basic. If you have any prior exposure to statistics or data concepts, you might find it too simplistic."
May be too simplistic for those with prior statistics knowledge.
"If you have any prior exposure to statistics or data concepts, you might find it too simplistic."
"I expected a bit more challenge or deeper dives into certain topics, even conceptually."
"If you're looking for something that teaches you how to *do* data analysis with software, this isn't it..."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in How to Describe Data with these activities:
Review Basic Probability and Statistics
Ensure a solid foundation by reviewing the fundamentals of probability and statistics before starting the course.
Browse courses on Probability
Show steps
  • Review concepts such as probability distributions, hypothesis testing, and regression.
  • Solve practice problems to reinforce your understanding.
Read "How to Lie with Statistics"
Become aware of the potential pitfalls and biases in statistics to make more informed decisions based on data.
Show steps
  • Read and understand the main arguments of the book.
  • Identify examples of misleading statistics in everyday life.
Excel Math
Refine your Excel skills to ensure that you are ready for this course.
Show steps
  • Review basic Excel functions and formulas
  • Develop proficiency in data manipulation techniques
Six other activities
Expand to see all activities and additional details
Show all nine activities
Learn Data Visualization Techniques
Enhance your ability to present data effectively by learning industry-standard data visualization techniques.
Browse courses on Data Visualization
Show steps
  • Explore different types of data visualizations.
  • Learn best practices for choosing the right visualization for different types of data.
  • Gain proficiency in using a data visualization tool.
Solve Real-World Data Problems
Hone your data analysis skills by solving problems that mirror real-world scenarios.
Browse courses on Data Analysis
Show steps
  • Identify the problem and define the variables.
  • Collect and clean the data.
  • Analyze the data using statistical techniques.
  • Interpret the results and draw conclusions.
Create a Data Story
Develop your ability to communicate data insights effectively by creating a compelling data story.
Browse courses on Data Storytelling
Show steps
  • Choose a dataset that interests you.
  • Explore the data and identify patterns and trends.
  • Develop a narrative that explains the insights you've found.
  • Create a visual representation of your data story.
Join a Study Group
Connect with fellow learners to discuss course concepts, share insights, and support each other's learning.
Show steps
  • Find a study group or create your own.
  • Meet regularly to discuss course materials.
  • Work together on assignments or projects.
Volunteer at a Data Analytics Organization
Gain hands-on experience and make a meaningful contribution by volunteering your skills at a data analytics organization.
Browse courses on Data Analytics
Show steps
  • Research and identify volunteer opportunities.
  • Apply for and secure a volunteer position.
  • Contribute to data analytics projects under the guidance of experienced professionals.
Contribute to Open-Source Data Projects
Enhance your skills and contribute to the data community by getting involved in open-source data projects.
Browse courses on Open Source
Show steps
  • Identify open-source data projects that align with your interests.
  • Review the project documentation and code.
  • Contribute to the project by fixing bugs or adding new features.

Career center

Learners who complete How to Describe Data will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to How to Describe Data.
Excel Skills for Statistics and Data Analysis: Essentials
Most relevant
Preparing and Aggregating Data for Visualizations using...
Most relevant
Application of Data Analysis in Business with R...
Most relevant
Understanding Basic SQL Syntax
Most relevant
The Structured Query Language (SQL)
Most relevant
Visualizing Data with Google Data Studio
Most relevant
Running Distributed TensorFlow using Vertex AI
Most relevant
Create Social Media Dashboards in Tableau
Most relevant
Optimizing Performance of LookML Queries
Most relevant

Coursera Buyer Protection & Guarantee

Verified partner policies & purchase protections

Accredited University Partner
Free Trial & Audit

7-Day Free Trial & Free Audit

7-day free trial on monthly Coursera Plus subscriptions; free audit option available on most individual courses to explore video lectures and readings at no charge.

Return & Refund Policy

14-Day Refund Guarantee

14-day refund window on annual Coursera Plus subscriptions and single-course purchases prior to certificate issuance. Monthly subscriptions do not offer refunds once billed.

Buyer Protections

Verified Academic & Industry Partner

Accredited university and industry certifications (e.g. Stanford, Google, IBM, Yale), secure SSL payment processing, and verifiable digital certificate links.

Key Purchase Protections
14-day refund window on annual Coursera Plus and single courses
7-day free trial on monthly Coursera Plus subscriptions
Free course audit option for lectures and readings
Verified certificates from top universities & companies
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser