Learning Goal: I’m working on a r exercise and need an explanation and answer to
Learning Goal: I'm working on a r exercise and need an explanation and answer to help me learn.Which of the following would be acceptable formats for implementing a logistic regression of dichotomous response variable y versus continuous predictor x? LM (y~x, family=”binomial”) GLM (y~x, family=”binomial”) Either Neither I have two models. Model A is a regression of dichotomous height (tall- or short) versus caloric intake (continous predictor). Model B is a regression of height as a continous measure agaisnt caloric intake (again, continous predictor). Model A (dichotomous height) has an AIC of 25; Model B (continous height) has an AIC of 50. What is true? Model A is a better model Model B is the better model We can compare model A versus B, but not enough information is provided We cannot comapre Model A versus Model B Suppose I wanted to extract the odds-ratio from a single-variable logistic regression (Suppose the logistic regression mode is called logit_mod)coef (logit_mod) exp (coef(logit_mod) ) predict (logit_mod) exp (predict (logit_mod) ) Suppose a linear regression of response where a second predictor is added, i.e. Model 1 = Y~a, and Model 2 = y~a+b. Which is true: The multiple-R-squared of Model 1 cannot be larger than that of Model 2 The multiple-R-squared of Model 1 cannot be smaller than that of Model 2 The adjusted-R-squared of Model 1 cannot be larger than that of Model 2 The adjusted-R-squared of Model 1 cannot be smaller than that of Model 2 What is true about regression model optimization routines? We should remove variables known to be uninformative before optimizing The Akaike information Criterion is optimized when it is at its largest value Both of the above are true Neither of the above are true Requirements: 1-2 sentences