Search result for Probability and Statistics Online Courses & Certifications
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Causal Inference
by Michael E. Sobel- 3.3
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Approx. 12 hours to complete
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, policy, and business. We will study methods for collecting data to estimate causal relationships. Students will learn how to distinguish between relationships that are causal and non-causal; this is not always obvious....
Statistics for Genomic Data Science
by Jeff Leek, PhD- 4.2
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Approx. 9 hours to complete
An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University. Module 1 Welcome to Statistics for Genomic Data Science What is Statistics? Finding Statistics You Can Trust (4:44) Getting Help (3:44) What is Data?...
Response Surfaces, Mixtures, and Model Building
by Douglas C. Montgomery- 4.7
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Approx. 13 hours to complete
Factorial experiments are often used in factor screening. ; that is, identify the subset of factors in a process or system that are of primary important to the response. Once the set of important factors are identified interest then usually turns to optimization; that is, what levels of the important factors produce the best values of the response....
Advanced Linear Models for Data Science 1: Least Squares
by Brian Caffo, PhD- 4.4
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Approx. 8 hours to complete
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models....
Improving Your Statistical Questions
by Daniel LakensTop Instructor- 4.9
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Approx. 18 hours to complete
This course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions....
Power and Sample Size for Multilevel and Longitudinal Study Designs
by Albert Ritzhaupt- 4.4
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Approx. 24 hours to complete
Power and Sample Size for Longitudinal and Multilevel Study Designs, a five-week, fully online course covers innovative, research-based power and sample size methods, and software for multilevel and longitudinal studies. The power and sample size methods and software taught in this course can be used for any health-related, or more generally, social science-related (e....
Causal Inference 2
by Michael E. Sobel- 0.0
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Approx. 6 hours to complete
This course offers a rigorous mathematical survey of advanced topics in causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. We will study advanced topics in causal inference, including mediation, principal stratification, longitudinal causal inference, regression discontinuity, interference, and fixed effects models....
Mathematical Biostatistics Boot Camp 2
by Brian Caffo, PhD- 4.4
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Approx. 12 hours to complete
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples. Hypothesis Testing Hypothesis Testing More Hypothesis Testing General Rules of Hypothesis Testing Two-sided Tests Confidence Intervals & P Values Power Calculating Power T Tests & Monte Carlo Two Sample Tests - Matched Data I Two Sample Tests - Matched Data II...
Random Models, Nested and Split-plot Designs
by Douglas C. Montgomery- 4.6
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Approx. 9 hours to complete
Many experiments involve factors whose levels are chosen at random. A well-know situation is the study of measurement systems to determine their capability. This course presents the design and analysis of these types of experiments, including modern methods for estimating the components of variability in these systems. Unit 1: Experiments with Random Factors...
Statistics with R Capstone
by Merlise A Clyde , Colin Rundel , David Banks , Mine Çetinkaya-Rundel- 4.6
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Approx. 6 hours to complete
The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. The analysis will implement both frequentist and Bayesian techniques and discuss in context of the data how these two approaches are similar and different, and what these differences mean for conclusions that can be drawn from the data....
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