# Data Science: Probability

## Rafael Irizarry, HarvardX

Learn probability theory -- essential for a data scientist -- using a case study on the financial crisis of 2007-2008.

In this course, part of our Professional Certificate Program in Data Science,you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007-2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

We will introduce important concepts such as random variables, independence, Monte Carlo simulations, expected values, standard errors, and the Central Limit Theorem. These statistical concepts are fundamental to conducting statistical tests on data and understanding whether the data you are analyzing is likely occurring due to an experimental method or to chance.

Probability theory is the mathematical foundation of statistical inference which is indispensable for analyzing data affected by chance, and thus essential for data scientists.

### What will you learn

• Important concepts in probability theory including random variables and independence
• How to perform a Monte Carlo simulation
• The meaning of expected values and standard errors and how to compute them in R
• The importance of the Central Limit Theorem

Dates:
• 15 July 2020
Course properties:
• Free:
• Paid:
• Certificate:
• MOOC:
• Video:
• Audio:
• Email-course:
• Language: English

### Reviews

No reviews yet. Want to be the first?

Register to leave a review

More on this topic:
Algorithms: Design and Analysis, Part 1
In this course you will learn several fundamental principles of algorithm design...
Algorithms: Design and Analysis, Part 2
In this course you will learn several fundamental principles of advanced algorithm...
Algorithms, Part I
This course covers the essential information that every serious programmer needs...
Algorithms, Part II
This course covers the essential information that every serious programmer needs...
Analysis of Algorithms
This course teaches a calculus that enables precise quantitative predictions...
More from 'Mathematics, Statistics and Data Analysis':
SP21: Introduction to Analytics Modeling
Learn essential analytics models and methods and how to appropriately apply...
SP21: Data Analytics for Business
This course prepares students to understand business analytics and become leaders...
UX Evaluation
Master UX evaluation using a variety of skill sets and methods. Uncover the...
L'évaluation UX
Maîtrisez l'évaluation UX en utilisant une variété de compétences et de méthodes...
Manufacturing Systems II
Learn how to analyze manufacturing systems to optimize performance and control...
More from 'edX':
Design Thinking Capstone
Demonstrate the knowledge and skills gained during the Design Thinking MicroMasters...
SP21: Computing for Data Analysis
A hands-on introduction to basic programming principles and practice relevant...
SP21: Introduction to Analytics Modeling
Learn essential analytics models and methods and how to appropriately apply...
SP21: Data Analytics for Business
This course prepares students to understand business analytics and become leaders...
China’s Communist Political System and Global Ambitions – A Deep Dive
You will gain a thorough understanding of how China’s political system works...

© 2013-2019