How to Describe Data (Coursera)

How to Describe Data (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.
This course is part of the Understanding Data: Navigating Statistics, Science, and AI Specialization.

What you'll learn

  • Learn the fundamentals of data interpretation, collection, and summarization
  • Learn the capabilities and limitations of data and discuss criteria for determining which statistics are reliable
  • Learn to interpret and evaluate the effectiveness of data visualizations

Syllabus

Welcome, Introduction & What Makes a Statistic Useful?
Module 1: Rethinking Certainty
Module 2: Talking about Numbers
Module 3: Statistics, Skepticism and Trust

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Mathematical Biostatistics Boot Camp 1 (Coursera) Coursera
Johns Hopkins University

Mathematical Biostatistics Boot Camp 1 (Coursera)

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

Sep 14th 2026
4 Weeks
Principles of fMRI 2 (Coursera) Coursera
Johns Hopkins University,University of Colorado Boulder

Principles of fMRI 2 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data.

Sep 21st 2026
4 Weeks
Fundamentals of Data Analysis in Excel (Coursera) Coursera
Corporate Finance Institute

Fundamentals of Data Analysis in Excel (Coursera)

Excel is the most widely used analysis tool in the world and a great starting point for diving into data analysis. In this course, you’ll apply Excel’s native tools to structure your data into spreadsheets and tables. You’ll then analyze and produce insights from that data using pivot tables. Finally, you’ll visualize those insights by building a dashboard in Excel. You’ll apply these skills using modern functionality like dynamic array formulas, linked data types, and Ideas in Excel. You’ll work hands-on with real-world scenarios, using datasets pulled from financial statements and retail sales.

Sep 21st 2026
5-12 Weeks
Data Management for Clinical Research (Coursera) Coursera
Vanderbilt University

Data Management for Clinical Research (Coursera)

This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research. Understanding and implementing solid data management principles is critical for any scientific domain. Regardless of your current (or anticipated) role in the research enterprise, a strong working knowledge and skill set in data management principles and practice will increase your productivity and improve your science. Our goal is to use these modules to help you learn and practice this skill set.

Sep 14th 2026
5-12 Weeks
Causal Inference (Coursera) Coursera
Columbia University

Causal Inference (Coursera)

This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships.

Sep 21st 2026
5-12 Weeks
Data Science Math Skills (Coursera) Coursera
Duke University

Data Science Math Skills (Coursera)

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.

Sep 24th 2026
4 Weeks
SQL: A Practical Introduction for Querying Databases (Coursera) Coursera
IBM

SQL: A Practical Introduction for Querying Databases (Coursera)

Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and manipulating data in databases. A working knowledge of databases and SQL is a must for anyone who wants to start a career in Data Engineering, Data Warehousing, Data Analytics, Data Science or Business Intelligence. The purpose of this course is to help you learn and apply foundational and intermediate knowledge of the SQL language, and become familiar with many relational database (RDBMS) concepts along the way.

Sep 21st 2026
5-12 Weeks
Bioinformatic Methods I (Coursera) Coursera
University of Toronto

Bioinformatic Methods I (Coursera)

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Sep 21st 2026
5-12 Weeks
Analysis and Interpretation of Large-Scale Programs (Coursera) Coursera
Johns Hopkins University

Analysis and Interpretation of Large-Scale Programs (Coursera)

This course is for implementers, managers, funders, and evaluators of health programs targeting women and children in low- and middle-income countries as well as undergraduate and graduate students in health-related fields. Course participants will learn how to 1) transform quantitative components of an evaluation measurement plan into a sound analysis plan to address the evaluation questions, 2) conduct quantitative analyses of primary or secondary surveys or other available data, 3) interpret the meaning of the analysis results and their implications, and 4) disseminate the evaluation findings to program implementers, local and global stakeholders.

Sep 21st 2026
5-12 Weeks
Combining and Analyzing Complex Data (Coursera) Coursera
University of Maryland, College Park

Combining and Analyzing Complex Data (Coursera)

In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.

Sep 21st 2026
4 Weeks
Case studies in business analytics with ACCENTURE (Coursera) Coursera
ESSEC Business School

Case studies in business analytics with ACCENTURE (Coursera)

This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors. The objective is to give you an helicopter overview on what's happening in this field. You will see how the tools presented in the two previous courses of the Specialization are used in real life projects.

Sep 21st 2026
3 Weeks