Introduction to Statistics (saylor.org)

Offered by Saylor.org,
Introduction to Statistics (saylor.org)

The purpose of this course is to introduce you to the subject of statistics as a science of data. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding in complex data sets has been more of a challenge. In this course, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information.

This course will begin with a brief overview of the discipline of statistics and will then quickly focus on descriptive statistics, introducing graphical methods of describing data. You will learn about combinatorial probability and random distributions, the latter of which serves as the foundation for statistical inference. On the side of inference, we will focus on both estimation and hypothesis testing issues. We will also examine the techniques to study the relationship between two or more variables; this is known as regression.
By the end of this course, you should gain a sound understanding about what statistics represent, how to use statistics to organize and display data, and how to draw valid inferences based on data by using appropriate statistical tools.

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

Related Courses

Improving your statistical inferences (Coursera) Coursera
Eindhoven University of Technology

Improving your statistical inferences (Coursera)

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power.

Oct 5th 2026
5-12 Weeks
Linear Algebra II (saylor.org) Saylor Academy
Saylor.org

Linear Algebra II (saylor.org)

Linear algebra is the study of vector spaces and linear mappings between them. In this course, we will begin by reviewing topics you learned in Linear Algebra I, starting with linear equations, followed by a review of vectors and matrices in the context of linear equations.

Legacy Course
Self-Paced
Initiation à la théorie des distributions (Coursera) Coursera
École Polytechnique

Initiation à la théorie des distributions (Coursera)

Une fonction discontinue peut-elle être solution d'une équation différentielle? Comment définir rigoureusement la masse de Dirac (une "fonction" d'intégrale un, nulle partout sauf en un point) et ses dérivées? Peut-on définir une notion de "dérivée d'ordre fractionnaire"? Cette initiation aux distributions répond à ces questions - et à bien d'autres.

Oct 5th 2026
5-12 Weeks
Real Analysis II (saylor.org) Saylor Academy
Saylor.org

Real Analysis II (saylor.org)

Real Analysis II is the sequel to Saylor’s Real Analysis I, and together these two courses constitute the foundations of real analysis in mathematics. In this course, you will build on key concepts presented in Real Analysis I, particularly the study of the real number system and real-valued functions defined on all or part (usually intervals) of the real number line.

Legacy Course
Self-Paced
Calculus I (saylor.org) Saylor Academy
Saylor.org

Calculus I (saylor.org)

Calculus can be thought of as the mathematics of CHANGE. Because everything in the world is changing, calculus helps us track those changes. Calculus is among the most important and useful developments of human thought.

Self Paced
Self-Paced
Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera) Coursera
Duke University

Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera)

In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space.

Oct 5th 2026
5-12 Weeks
Information Theory (Coursera) Coursera
The Chinese University of Hong Kong

Information Theory (Coursera)

At the completion of this course, the student should be able to: demonstrate knowledge and understanding of the fundamentals of information theory; appreciate the notion of fundamental limits in communication systems and more generally all systems; develop deeper understanding of communication systems; apply the concepts of information theory to various disciplines in information science.

Oct 5th 2026
13-24 Weeks
Differential Equations (saylor.org) Saylor Academy
Saylor.org

Differential Equations (saylor.org)

Differential equations are, in addition to a topic of study in mathematics, the main language in which the laws and phenomena of science are expressed. In basic terms, a differential equation is an expression that describes how a system changes from one moment of time to another, or from one point in space to another.

Legacy Course
Self-Paced