Mathematical Biostatistics Boot Camp 1 free videos and free material uploaded by Johns Hopkins University Staff .
Introduction, Probability, Expectations, and Random Vectors
You are about to undergo an intense and demanding immersion into the world of mathematical biostatistics Over the next few weeks, you will learn about probability, expectations, conditional probabilities, distributions, confidence intervals, bootstrapping, binomial proportions, and much more Module 1 covers experiments, probability, variables, mass functions, density functions, cumulative distribution functions, expectations, variations, and vectors
Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics
This module covers Conditional Probability, Bayes' Rule, Likelihood, Distributions, and Asymptotics These are the most fundamental core concepts in mathematical biostatistics and statistics After this module you should be able to recognize and be functional in these key concepts
Confidence Intervals, Bootstrapping, and Plotting
This module covers Confidence Intervals, Bootstrapping, and Plotting These are core concepts in mathematical biostatistics and statistics After this module you should be able to recognize and be functional in these key concepts
Binomial Proportions and Logs
This module covers Binomial Proportions and Logs These are core concepts in mathematical biostatistics and statistics After this module you should be able to recognize and be functional in these key concepts
This class presents the fundamental probability and statistical concepts used in elementary data analysis It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus A small amount of linear algebra and programming are useful for the class, but not required
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