EdX

Statistics for Business Analytics: Probability (edX)

Statistics for Business Analytics: Probability (edX)

This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background. In this course, we explore the different ways of determining the probability of different events and outcomes. We want to be able to answer questions like: what is the probability that more than 90% of patients will show up for their appointments at a medical practice? what are the chances of a store having more than 20 customers in its first two hours of being open? how likely is it that a staff member will use 6 or fewer days of sick leave in a year?

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

This course is divided into three topics:

  • In Topic 1, we talk about the basics of probability – ideas like whether or not events can happen together, whether events can influence each other, and processes for calculating probabilities in simple situations.
  • Topic 2 is about conditional probability ; that is, the idea that we can become more certain about particular outcomes when we know the circumstances under which they are occurring.
  • In Topic 3, we discuss the "big 5" probability distributions ; powerful tools that can be used to calculate probabilities in a variety of complex situations. These distributions form the "heart" of the course and have practical applications in a wide range of real-life scenarios.

This course is part of the Statistics for Business Analytics Professional Certificate.

What you'll learn
Upon successful completion of this course, you will be able to:

  • Describe the basic concepts of probability.
  • Calculate basic probabilities for mutually exclusive, non-mutually exclusive and multiple independent events.
  • Calculate conditional probabilities in simple and complex situations.
  • Determine the probability of a given number of successes for discrete variables using binomial, Poisson and hypergeometric distributions.
  • Determine the probability of outcomes above or below a threshold for continuous variables using normal and exponential distributions.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Data Science and Basic Statistics for Business (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Introduction to Data Science and Basic Statistics for Business (edX)

In this course you will acquire statistical methods for decision making in business, as well as technological tools to develop quantitative skills. Areas such as " big data" require very clear knowledge of statistics and business, technology provides us various applications that require solid training in statistics for proper use and interpretation .

Self Paced
Self-Paced
MathTrackX: Statistics (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Statistics (edX)

Understand fundamental concepts relating to statistical inference and how they can be applied to solve real world problems. This course will build on probability and random variable knowledge gained from previous courses in the MathTrackX XSeries with the study of statistical inference, one of the most important parts of statistics.

Self Paced
Self-Paced
Mathematical understanding of uncertainty (edX) EdX
Seoul National University,SNUx

Mathematical understanding of uncertainty (edX)

This lecture series discusses how the concept of probability can be used to handle, control, and exploit uncertainty in the real-world. It is an undergraduate-level lecture series on probability, but is entirely different from the usual courses on probability theory. The lectures cover the basics of probability theory including the relevant mathematics, but instead of focusing on mathematics, the lectures explain how probability theory can help understand real-world uncertainty using various examples.

Self Paced
Self-Paced
Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX) EdX
Seoul National University,SNUx

Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX)

This course teaches basic statistical concepts and explores many compelling applications of statistical methods using real-life applications of Statistics. Why do we study statistics? The field of statistics provides professionals and scientists withconceptual foundations and useful techniques for evaluating ideas, testing theories, and - ultimately -uncovering the truth in any situation.

Self Paced
Self-Paced
Probability and Statistics III: A Gentle Introduction to Statistics (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics III: A Gentle Introduction to Statistics (edX)

This course provides an introduction to basic statistical concepts. We begin by walking through a library of probability distributions – including the normal distribution, which in turn leads to the Central Limit Theorem. We then discuss elementary descriptive statistics and estimation methods.

Self Paced
Self-Paced
Advanced statistical physics (edX) EdX
École Polytechnique Fédérale de Lausanne,EPFLx

Advanced statistical physics (edX)

We explore statistical physics in both classical and open quantum systems. Additionally, we will cover probabilistic data analysis that is extremely useful in many applications. This course covers non-equilibrium statistical processes and the treatment of fluctuation dissipation relations by Einstein, Boltzmann and Kubo. Moreover, the fundamentals of Markov processes, stochastic differential and Fokker Planck equations, mesoscopic master equation, etc will be treated in detail. Prior knowledge of statistical physics is highly recommended but not required.

Self Paced
Self-Paced
Statistical Inference and Modeling for High-throughput Experiments (edX) EdX
HarvardX,Harvard University

Statistical Inference and Modeling for High-throughput Experiments (edX)

A focus on the techniques commonly used to perform statistical inference on high throughput data. In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. We then introduce statistical modeling and how it is applied to high-throughput data. In particular, we will discuss parametric distributions, including binomial, exponential, and gamma, and describe maximum likelihood estimation.

Self Paced
Self-Paced
Introducción a Ciencias de Datos y Estadística Básica para Negocios (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Introducción a Ciencias de Datos y Estadística Básica para Negocios (edX)

En este curso adquirirás los métodos estadísticos para la toma de decisiones en los negocios, así como herramientas tecnológicas para desarrollar habilidades cuantitativas. Áreas como el “big data” requieren un conocimiento muy claro de la estadística; en las áreas de negocios, la tecnología pone a nuestro alcance diversas aplicaciones que requieren una sólida formación en estadística para su correcto uso e interpretación.

Self Paced
Self-Paced
Predictive Analytics (edX) EdX
Indian Institute of Management, Bangalore,IIMBx

Predictive Analytics (edX)

Master the tools of predictive analytics in this statistics based analytics course. Decision makers often struggle with questions such as: What should be the right price for a product? Which customer is likely to default in his/her loan repayment? Which products should be recommended to an existing customer? Finding right answers to these questions can be challenging yet rewarding.

Self Paced
5-12 Weeks
Data Science: Probability (edX) EdX
HarvardX,Harvard University

Data Science: Probability (edX)

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008. In this course, 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.

Self Paced
Self-Paced