Probability & Statistics
Showing 49–60 of 76 results
Introduction to Statistics
Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!
Introduction to Statistics in Google Sheets
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Introduction to Statistics in Python
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.
Linear Algebra for Data Science in R
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Mixture Models in R
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.
Modeling with Data in the Tidyverse
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Monte Carlo Simulations in Python
Learn to design and run your own Monte Carlo simulations using Python!
Multivariate Probability Distributions in R
Learn to analyze, plot, and model multivariate data.
Network Analysis in R
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Nonlinear Modeling with Generalized Additive Models (GAMs) in R
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
Performing Experiments in Python
Learn about experimental design, and how to explore your data to ask and answer meaningful questions.
Practicing Statistics Interview Questions in Python
Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.