Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.