When | Wednesday, April 24th, 2019 |
Where | Milam Hall, Room 213 |
Refreshments | 3:55 pm |
Seminar | 4:00 pm |
Cost | Free and open to the public |
Pitfalls of Modelling and Modelling Techniques
Statisticians must consider many things when developing a useful model. This starts as soon as one decides they want to build a model, from the objective of one's experiment, to pitfalls that can occur even after fitting a model. This talk will look at issues that can occur before, during, and after collecting the data, as well as issues inherent to several different common statistical and machine learning models, such as linear regression, classification/regression trees, and neural networks.