In a logistic regression model, the predictor a. is interval/ratio data.
b. must undergo a logarithmic transformation before undergoing logistic regression.
c. must be in the range of 0 to 1
d. represents ranked scores
e. must be a binary variable

B. must undergo a logarithmic transformation before undergoing logistic regression.

Step-by-step explanation:

A logistic regression model allows us to establish a relationship between a binary outcome variable and a group of predictor variables. It models the logit-transformed probability as a linear relationship with the predictor variables.

15

step-by-step explanation:

we are given the following expression and we are to solve it and find the product:

-13 × (-5)

solving the given expression in the standard order of solving a mathematical expression, beginning with the opening of brackets and then multiplying the terms and changing their signs.

-3 × -5 = 15 (answer is positive because when negative is multiplied with negative, it gives a positive answer)