Loved by learners at thousands of companies
Introduction to Statistics in R
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
Foundations of Probability in R
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.
Introduction to Regression in R
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Intermediate Regression in R
Learn to perform linear and logistic regression with multiple explanatory variables.
Generalized Linear Models in R
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.
Hypothesis Testing in R
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests.
Experimental Design in R
In this course you'll learn about basic experimental design, a crucial part of any data analysis.
A/B Testing in R
Learn A/B testing: including hypothesis testing, experimental design, and confounding variables.
Dealing With Missing Data in R
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.
Handling Missing Data with Imputations in R
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Analyzing Survey Data in R
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Survey and Measurement Development in R
Design surveys to get actionable insights via reviewing of survey design structures and visualizing and analyzing survey results.
Hierarchical and Mixed Effects Models in R
In this course you will learn to fit hierarchical models with random effects.
Survival Analysis in R
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!
Mixture Models in R
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.
Fundamentals of Bayesian Data Analysis in R
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Bayesian Regression Modeling with rstanarm
Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.
Bayesian Modeling with RJAGS
In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.
Factor Analysis in R
Explore latent variables, such as personality using exploratory and confirmatory factor analyses.
Structural Equation Modeling with lavaan in R
Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.
Foundations of Inference
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
Inference for Categorical Data in R
In this course you'll learn how to leverage statistical techniques for working with categorical data.
Inference for Numerical Data in R
In this course you'll learn techniques for performing statistical inference on numerical data.
Inference for Linear Regression in R
In this course you'll learn how to perform inference using linear models.