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How to Describe Data

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.

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What's inside

Syllabus

Welcome, Introduction & What Makes a Statistic Useful?

Rethinking Certainty

Talking about Numbers

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

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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

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Ensure a solid foundation by reviewing the fundamentals of probability and statistics before starting the course.

Browse courses on Probability

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Review concepts such as probability distributions, hypothesis testing, and regression.
Solve practice problems to reinforce your understanding.

Read "How to Lie with Statistics"

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Become aware of the potential pitfalls and biases in statistics to make more informed decisions based on data.

View How to Lie with Statistics on Amazon

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Read and understand the main arguments of the book.
Identify examples of misleading statistics in everyday life.

Excel Math

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Refine your Excel skills to ensure that you are ready for this course.

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Review basic Excel functions and formulas
Develop proficiency in data manipulation techniques

Six other activities

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Learn Data Visualization Techniques

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Enhance your ability to present data effectively by learning industry-standard data visualization techniques.

Browse courses on Data Visualization

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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

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Hone your data analysis skills by solving problems that mirror real-world scenarios.

Browse courses on Data Analysis

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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

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Develop your ability to communicate data insights effectively by creating a compelling data story.

Browse courses on Data Storytelling

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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

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Connect with fellow learners to discuss course concepts, share insights, and support each other's learning.

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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

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Gain hands-on experience and make a meaningful contribution by volunteering your skills at a data analytics organization.

Browse courses on Data Analytics

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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

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Enhance your skills and contribute to the data community by getting involved in open-source data projects.

Browse courses on Open Source

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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'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 How to Describe Data.

Python for Data Analysis

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The third edition of the essential guide to data wrangling with pandas, NumPy, and Jupyter in Python. Updated for newer versions of the libraries, this book remains a core resource for anyone performing data analysis in Python. It widely used textbook and reference for its clear explanations and practical examples.

How to Describe Data

Two deals to help you save

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Broad data literacy for beginners

Activities

Career center

Reading list

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