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Mixture Models in R
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.
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Probability Puzzles in R
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
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Bayesian Modeling with RJAGS
In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.
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Multivariate Probability Distributions in R
Learn to analyze, plot, and model multivariate data.
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Inference for Numerical Data in R
In this course you'll learn techniques for performing statistical inference on numerical data.
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GARCH Models in R
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
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Case Studies in Statistical Thinking
Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.
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Bayesian Regression Modeling with rstanarm
Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.
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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.
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Inference for Categorical Data in R
In this course you'll learn how to leverage statistical techniques for working with categorical data.
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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.
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Inference for Linear Regression in R
In this course you'll learn how to perform inference using linear models.
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A/B Testing in R
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
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Survival Analysis in Python
Use survival analysis to work with time-to-event data and predict survival time.
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Dimensionality Reduction in R
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
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Factor Analysis in R
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
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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!
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Practicing Statistics Interview Questions in R
In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.
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Statistical Simulation in Python
Learn to solve increasingly complex problems using simulations to generate and analyze data.
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ARIMA Models in R
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
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Foundations of Inference in Python
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.
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GARCH Models in Python
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
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Forecasting in R
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.
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Hierarchical and Mixed Effects Models in R
In this course you will learn to fit hierarchical models with random effects.