Statistical Learning with Python - Statistical Learning: 3.4 Some important questions

Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing Trevor Hastie, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/people/trevor-j-hastie Robert Tibshirani, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/people/robert-tibshirani Jonathan Taylor, Professor Statistics at Stanford University - https://statistics.stanford.edu/people/jonathan-taylor You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion. You can choose to take the course in R (https://www.edx.org/course/statistica) or in Python (https://www.edx.org/learn/data-analysis-statistics/stanford-university-statistical-learning-with-python) For more information about courses on Statistics, you can browse our Stanford Online Catalog: https://stanford.io/3QHRi72 0:00 Some important questions 1:02 Is at least one predictor useful? 3:02 Deciding on the important variables 4:41 Forward selection 7:46 Other Considerations in the Regression Model 9:34 Qualitative Predictors - continued 11:49 Qualitative predictors with more than two levels 14:04 Results for ethnicity