Linear regression modeling is an extremely powerful data analysis tool, useful for a variety of inferential tasks such as prediction, parameter estimation and data description. In this section we give a very brief introduction to the linear regression model and the corresponding Bayesian approach to estimation. Additionally, we discuss the relationship between Bayesian and ordinary least squares regression estimates.
KeywordsOxygen Uptake Posterior Distribution Prior Distribution Linear Regression Model Maximal Oxygen Uptake
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