Answer:
(B) multicollinearity is present.
Explanation:
Multicollinearity -
It is the process where , one of the predictor variable in the multiple regression model can be linearly predicted from the others with the substantial degree of accuracy , is known as multicollinearity or collinearity .
<u>In this case , the coefficient estimated of the multiple regression can change erratically for even a small change in the model .</u>
hence , from the question , the indication is of (B) multicollinearity is present .
Answer:
b. other than 1
Explanation:
Nonlinear models are called that way because they are not linear in parameters. In order for this nonlinear characteristic to exist, the exponents of the parameters must be any number other than 1.
While linear models can have a nonlinear relationship between the predictors and independent variables. But when you analyze the mean (predictor), it must be linear with the parameters.
Answer:
c) 82.33 is the percentage decrease in revenue from tourist to Florida
<span>Of the over-27 million businesses, only 18,500 employ over 500 employees. 18,500/27.3mil = 0.0678%, so subtracting that from 100% leaves 99.9322% of all companies having a workforce under 500 employees. These are the "small businesses."</span>
