Logistic regression (categorical outcomes)

THis final lecture on the module is the last lecture before students break up for the winter vacation and, consequently, has a seasonal theme that will be weird if you're watching at some other time of year. Nevertheless, we look at logistic regression and how the linear model adapts to deal with predicting outcomes that are categorical. We talk about logs (not Christmas ones), odds ratios, and fit the models using R. We look at two examples, one with a categorical predictor and one with a categorical and continuous predictor. There's quite a lot of non-statistical randomness that may or may not be to your taste. Learn R alongside these lectures with the discovr package (https://www.discovr.rocks/discovr/) Suggested soundtrack: Wizzard: I wish it could be Christmas everyday (   • Wizzard - I Wish It Could Be Christmas Eve...  ) Acknowledgements: Green screen snow effect by    / creativefilmcc   Green screen fairy sparkles by    / @jaysgreenscreenandsoundeff5048