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

Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Sep 21st 2026
5-12 Weeks
Calculus: Single Variable Part 4 - Applications (Coursera) Coursera
University of Pennsylvania

Calculus: Single Variable Part 4 - Applications (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences.

Sep 28th 2026
5-12 Weeks
Statistics and Data Analysis with Excel, Part 1 (Coursera) Coursera
University of Colorado Boulder

Statistics and Data Analysis with Excel, Part 1 (Coursera)

Designed for students with no prior statistics knowledge, this course will provide a foundation for further study in data science, data analytics, or machine learning. Topics include descriptive statistics, probability, and discrete and continuous probability distributions. Assignments are conducted in Microsoft Excel (Windows or Mac versions). Designed to be taken with the follow-up course, “Statistics and Data Analysis with Excel, Part 2.”

Sep 28th 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
Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera) Coursera
University of Colorado Boulder

Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera)

This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.

Sep 21st 2026
5-12 Weeks
Construção de Relacionamentos em Vendas Orientada a Dados (Coursera) Coursera
FIA Business School

Construção de Relacionamentos em Vendas Orientada a Dados (Coursera)

Nossas boas-vindas ao Curso Construção de Relacionamento em Vendas Orientada a Dados. Neste curso, você aprenderá métodos sobre data analytics para o ambiente dos profissionais de vendas. Ao final deste curso, você será capaz de avaliar relacionamentos entre o desempenho de vendas e os gastos relacionados; agrupar por semelhança itens, produtos ou serviços e, por fim, realizar recomendações de produtos para clientes sob características preestabelecidas.

Sep 28th 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
Gestión del análisis de datos (Coursera) Coursera
Johns Hopkins University

Gestión del análisis de datos (Coursera)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results.

Sep 21st 2026
1 Week
Gender Foundations in Health Data: A Data for Health Course (Coursera) Coursera
Johns Hopkins University

Gender Foundations in Health Data: A Data for Health Course (Coursera)

Welcome to Gender Foundations in Health Data: A Data for Health course. This course was developed from an online seminar series of the same name, that was hosted by Johns Hopkins University Bloomberg School of Health in 2021-22. The course instructors are Drs. Michelle Kaufman and Tahilin Sanchez Karver. This course will raise learners' awareness of the necessity of utilizing a gender lens in global public health data, policy, and practice, feature how-tos and key examples of integration of gender in data collection, analysis, and use from Data for Health partners.

Sep 28th 2026
1 Week
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