31. This model assumes that each group has a different regression model -with its own intercept and slope. 32. The standard assumptions of the linear regression model are also assumed to hold, as discussed below. 33. An important consideration when carrying out statistical inference using regression models is how the data were sampled. 34. Start with a regression model where the outcome Y _ i is impacted by X _ i 35. Binomial regression models are essentially the same as binary choice models, one type of discrete choice model. 36. The site predicts game outcomes and rates teams using a logistic regression model based on team efficiency statistics. 37. In empirical studies, these implicit characteristic prices are coefficients that relate prices and attributes in a regression model . 38. In particular, least squares estimates for regression models are highly sensitive to ( not robust against ) outliers. 39. Mahalanobis distance and leverage are often used to detect outliers, especially in the development of linear regression models . 40. An alternative approach to probability calibration is to fit an isotonic regression model to an ill-calibrated probability model.
