Multiple Choice Questions 34-35 Below is an incomplete table of ANOVA for a linear regression model. Analysis of variance Source DF SS MS F-statistic Regression  1 920.45 920.45 ? Residual 8 18.91 ? Total 9 939.36 Using the above table, answer Questions 34 and 35.  

Which of the options below is NOT a common sign of multicollinearity in linear regression?

When performing variable selection, BIC usually tends to select models with more predicting variables than AIC.

When working to create a logistic regression model, an analyst is considering two models: Model 1 includes only one predicting variable A. Model 2 includes variable A in addition to predicting variable B. The analyst notices that the sign of the estimated coefficient for A is negative in model 1 and positive in model 2. This is most likely because:

Poisson regression is an example of a generalized linear model where the link function is the exponential function.

Bob fitted a Poisson regression model between the response and the predicting variable . The estimated coefficients are

Adding more predictors to a multiple linear regression model might lead to a smaller .  

To apply Poisson regression, the response variable must take non-negative integer values only.

K-fold cross-validation is a common approach to select the optimal penalty constant lambda (

When we test whether a subset of coefficients is zero in logistic regression, the test statistic (the difference between the log-likelihoods for the full model and the reduced model) approximately follows an F-distribution.