16- A regression was performed to predict the Selling Price of a yacht in thousands of dollars based on the number of Rooms it had, its Age (years), and its Length (feet). The R²is 68.45%. The equation is given here.

Selling Price = 120.51 + 7.46 Rooms - 1.78 Age + 2.83 Length

Which of the following statements is true?

The selling price of an individual yacht cannot be predicted with this model.

For a givenAgeandLength, every extra room is associated with an additional $7,460 in the average selling price of the yacht.

The model fits 68.45% of the data.

The price of a yacht decreases 1.78 times with every year it ages.

Every additional foot ofLengthcauses the selling price of the yacht to increase 2.83 times.

17-According to a large-scale survey of Canadians, the probability that the family owns two cars if their family income is over $50,000 is .50. Of the households surveyed, 40 percent had incomes over $50,000 and 30% had two cars. What is the probability that a family has two cars and an income of over $50,000 a year?

0.12

None of the other answers is correct

0.15

0.30

0.20

18-If all the points in a scatter diagram do not lie on the least-squares regression line, then the coefficient of correlation must be either less than +1.0, and more than -1.0

Select one:

True

False

36--A small value of F indicates that most of the variation in y is explained by the regression equation and that the model is useful.

Select one:

True

False

34-When an explanatory variable is dropped from a multiple regression model, the coefficient of determination can increase.

Select one:

True

False