: You are interested in predicting the probability that an NCAA men’s basketball team wins their first round game in the annual NCAA men’s basketball tournament, where potential predictors of the binary indicator of winning the first game include a variety of team-level variables measured for each of the 64 teams competing in the first round. There is only one observation per team, and the dependent variable is a binary indicator (1, 0) of whether the team won their first round game. View
: What model should we use when our target outcome, or dependent variable is binary, or only has two outputs, 0 and 1? View
: What most likely happened to our R-Squared value when we added the third predictor LSTAT to our initial model? View
: Which values for DMDEDUC2x and RIAGENDRx are represented in our intercept, or what is our reference level? View
: What type of model should we use when our target outcome, or dependent variable, is continuous? View
: Are the predictors for this model statistically significant, yes or no? (Hint: What are their p-values?) View
: Fill in the blanks. With 95% confidence, I estimate that the increase in log odds of smoking 100+ cigarettes for each increase by one in BMI, while holding Age constant, is between ____ and ____, on average. View
: We’d like to predict the log odds of smoking 100+ cigarettes for a given individual using the logistic regression model with the two variables: BMI and Age. For an individual with a BMI of 22 who is 45 years old, what would the predicted log odds be? View
: The sample of adults surveyed in NHANES contains adults age 20-80 with BMIs of 14.5-64.6. For the individual with a BMI of 22 who is 45 years old, do you trust the predicted log odds calculated above as being reasonable? View
