such as linear regression, are easily interpretable, but inflexible, in that they don't capture many real-world relationships accurately. Other models, such as neural networks, are quite flexible, but ...

class Additive (param=ref ref='4'); model y=Additive / covb; title1 'Multiple Response Cheese Tasting Experiment'; run; Results of the analysis are shown in Output 39.2.1, and the estimated covariance ...

you will learn to use intermediate and advanced statistical modeling techniques, including the theory and application of linear regression analysis, ANOVA and experimental design, and generalized ...