Learn fundamental concepts of mathematical probability to prepare for a career in the growing field of information and data science.

Learn about probability distribution models, including normal distribution, and continuous random variables to prepare for a career in information and data science.

Master sampling to get more accurate statistics with less data.

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Build the foundation you need to think statistically and to speak the language of your data.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Delve into statistical theory and its applications in data analysis and research methodologies.

Master the fundamentals of statistics with Statistics 101. Learn key concepts like probability, hypothesis testing, and statistical inference, and apply them to real-world data analysis and decision-making scenarios in various industries.

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

Use survival analysis to work with time-to-event data and predict survival time.

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Learn the core techniques necessary to extract meaningful insights from time series data.