1. The existence of non-negativity constraints in a two-variable linear program implies that we are always working in the northwest quadrant of a graph.

a. True

b. False

2.

When the significance level is small enough in the F-test, we can reject the null hypothesis that there is no linear relationship.

	a.	True
	b.	False

3.

The existence of non-negativity constraints in a two-variable linear program implies that we are always working in the northwest quadrant of a graph.

	a.	True
	b.	False

4. The value of r² can never decrease when more variables are added to the model.

	a.	True
	b.	False

5. In a linear program, the constraints must be linear, but the objective function may be nonlinear.

a.

True

b. False

6.

The error standard deviation is estimated by MSE.

	a.	True
	b.	False

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