Statistics & Probability Courses and Certifications

The Royal Institution

How Not to Fall for Bad Statistics - With Jennifer Rogers

Learn to question sensational health headlines by distinguishing correlation from causation, relative from absolute risk, and uncertainty in reported statistics.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

AnalystPrep

Normal and Lognormal Distributions for SOA Exam P

Master normal and lognormal distributions, their properties, and calculations of expected values, variance, moments, mode, median, and percentiles for SOA Exam P preparation.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Fundamentals of Statistics

10 ratings

Develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing and prediction. -- Part of the MITx MicroMasters program in Statistics and Data Scien

• edX
• 17 weeks, 10-14 hours a week
• Self-Paced
• Free Online Course (Audit)

Estadística y probabilidad

1720 ratings at Coursera

Curso introductorio que desarrolla la representación e interpretación de datos, el análisis bivariado y la probabilidad mediante ejemplos contextualizados.

• Coursera
• 4 weeks, 5 hours a week
• Self-Paced
• Paid Course

Introduction to Linear Models and Matrix Algebra

12 ratings

Learn to use R programming to apply linear models to analyze data in life sciences.

• edX
• 4 weeks, 2-4 hours a week
• Self-Paced
• Free Online Course (Audit)

Sampling in Python

3905 ratings at DataCamp

Sampling in Python is the cornerstone of inference statistics and hypothesis testing.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Hypothesis Testing in Python

3678 ratings at DataCamp

Hypothesis testing lets you answer questions about your datasets in a statistically rigorous way.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Introduction to Regression with statsmodels in Python

3026 ratings at DataCamp

Use Python statsmodels For Linear and Logistic Regression Linear regression and logistic regression are two of the most widely used statistical models.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Learn Python for Healthcare Statistics

4 ratings

Use Python in Google Colab for healthcare statistics, including summary statistics, hypothesis testing, sampling distributions, and linear models.

• YouTube
• 8 hours
• Self-Paced
• Free Video

Experimental Design in Python

1899 ratings at DataCamp

Implement Experimental Design Setups Learn how to implement the most appropriate experimental design setup for your use case.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Introduction to Regression in R

1522 ratings at DataCamp

Linear regression and logistic regression are the two most widely used statistical models and act like master keys, unlocking the secrets hidden in datasets.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Hypothesis Testing in R

1033 ratings at DataCamp

Discover Hypothesis Testing in R Hypothesis testing lets you ask questions about your datasets and answer them in a statistically rigorous way.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

London School of Economics and Political Science

Statistics 2 Part 1: Probability and Distribution Theory

The third in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further st

• edX
• 5 weeks, 12-15 hours a week
• Self-Paced
• Free Online Course (Audit)

College Mathematics Series Courses II ——Linear algebra & probability and statistics

A university foundation course combining linear algebra, data organization, and probability concepts to build systematic mathematical problem-solving skills.

• XuetangX
• Self-Paced
• Free Online Course

Great Learning

Essential Statistics for Data Science - Learn Statistics for Data Science

1 rating

An intensive introduction to statistics for data science, covering descriptive measures, Python-based concepts, distributions, hypothesis testing, ANOVA, and chi-square tests.

• YouTube
• 5 hours 26 minutes
• Self-Paced
• Free Video