Udacity

Intro to Statistics (Udacity)

Offered by Udacity,
Intro to Statistics (Udacity)

Get ready to analyze, visualize, and interpret data! Thought-provoking examples and chances to combine statistics and programming will keep you engaged and challenged.

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

Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.
This course will cover visualization, probability, regression and other topics that will help you learn the basic methods of understanding data with statistics.

Syllabus

Lesson 1
Visualizing relationships in data
Seeing relationships in data.
Making predictions based on data.
Simpson's paradox.

Lesson 2
Probability
Introduction to Probability.
Bayes Rule.
Correlation vs. Causation.

Lesson 3
Estimation
Maximum Likelihood Estimation.
Mean, Median, Mode.
Standard Deviation and Variance.

Lesson 4
Outliers and Normal Distribution.
Outliers, Quartiles.
Binomial Distribution.
Manipulating Normal Distribution.

Lesson 5
Inference
Confidence Intervals.
Hypothesis Testing.

Lesson 6
Regression
Linear regression.
Correlation.

Lesson 7
Final Exam

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

Related Courses

Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

Statistics & Data Analysis Data Science

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Nov 9th 2026
4 Weeks
IPython Data Analysis Computer Programming
Details
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Statistics & Data Analysis

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 design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Nov 9th 2026
4 Weeks
Medicine Statistics Data Analysis
Details
Real-Time Analytics with Apache Storm (Udacity) Udacity
Udacity,Twitter

Real-Time Analytics with Apache Storm (Udacity)

Statistics & Data Analysis Data Science

The world is trending in real time! Learn from Twitter to scalably process tweets, or any big data stream, in real-time to drive d3 visualizations using Apache Storm, the "Hadoop of Real Time." Storm is free, open source, and fun to use! Learn from Karthik Ramasamy, about the distributed, fault-tolerant, and flexible technology used to power Twitter’s real-time data flow pipeline. Twitter open sourced Storm in 2011, and it graduated to a top-level Apache project in September, 2014.

Self Paced
Self-Paced
Data Analysis Hadoop Data Science
Details
Data Analysis with R (Udacity) Udacity
Udacity,Facebook

Data Analysis with R (Udacity)

Statistics & Data Analysis

Visually Analyze and Summarize Data Sets. Exploratory data analysis is an approach for summarizing and visualizing the important characteristics of a data set. Promoted by John Tukey, exploratory data analysis focuses on exploring data to understand the data’s underlying structure and variables, to develop intuition about the data set, to consider how that data set came into existence, and to decide how it can be investigated with more formal statistical methods.

Self Paced
Self-Paced
Statistics Data Analysis EDA
Details
Data Visualization and D3.js (Udacity) Udacity
Udacity,Zipfian Academy

Data Visualization and D3.js (Udacity)

Statistics & Data Analysis Data Science

Communicating with Data. Learn the fundamentals of data visualization and practice communicating with data. This course covers how to apply design principles, human perception, color theory, and effective storytelling to data visualization. If you present data to others, aspire to be an analyst or data scientist, or if you’d like to become more technical with visualization tools, then you can grow your skills with this course.

Self Paced
Self-Paced
Storytelling Data Analysis Color Theory
Details
Think Again III: How to Reason Inductively (Coursera) Coursera
Duke University

Think Again III: How to Reason Inductively (Coursera)

Personal and Professional Development

Want to solve a murder mystery? What caused your computer to fail? Who can you trust in your everyday life? In this course, you will learn how to analyze and assess five common forms of inductive arguments: generalizations from samples, applications of generalizations, inference to the best explanation, arguments from analogy, and causal reasoning. The course closes by showing how you can use probability to help make decisions of all sorts.

Nov 9th 2026
4 Weeks
Probability Personal Development Reason
Details
Estadística aplicada a los negocios (Coursera) Coursera
Universidad Austral

Estadística aplicada a los negocios (Coursera)

Statistics & Data Analysis Data Science

La toma de decisiones está en la esencia de los negocios. Gerenciar es tomar decisiones, muchas veces bajo presión, con información desordenada y en un contexto de incertidumbre. Un aspecto básico es entender y analizar la información, organizar los datos de forma de facilitar su posterior uso y la toma de decisiones.

Nov 9th 2026
4 Weeks
Business Statistics Decision Making
Details