Name: Estimating Model Parameters - Model Errors and Randomness
Uploaded: 2021-01-26T00:00:00Z
Description: In our final chapter, we introduce concepts from inferential statistics, and use them to explore how maximum likelihood estimation and bootstrap resampling can be used to estimate linear model parameters. We then apply these methods to make probabilistic statements about our confidence in the model parameters.