This Specialization is intended for all learners seeking to develop proficiency in statistics, Bayesian statistics, Bayesian inference, R programming, and much more. Through four complete courses (From Concept to Data Analysis; Techniques and Models; Mixture Models; Time Series Analysis) and a culminating project, you will cover Bayesian methods — such as conjugate models, MCMC, mixture models, and dynamic linear modeling — which will provide you with the skills necessary to perform analysis, engage in forecasting, and create statistical models using real-world data.
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Get Started / More InfoStatistical modeling lies at the heart of data science. Well crafted statistical models allow data scientists to draw conclusions about the world from the limited...
This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine,...
Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us...
In this course, you will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to perform...