Question

Point out the wrong statement.

(a) Additive response models don’t make much sense if the response is discrete, or strictly positive

(b) Transformations are often easy to interpret in linear model

(c) Regression models are used to predict one variable from one or more other variables

(d) All of the mentioned

I had been asked this question during an online interview.

The doubt is from Binary and Count Outcomes topic in portion Statistical Inference and Regression Models of Data Science

Answer 1

Correct option is (b) Transformations are often easy to interpret in linear model

Explanation: Transformations are often hard to interpret in linear model.