109. Simple Regression

1. In simple linear regression analysis with X Representing the independent variable and Y Representing the dependent variable, if the Y Intercept is negative, then

(a) the correlation between X And Y Is negative.

(b) the correlation between X And Y Is positive.

(c) the correlation between X And Y Could be either negative, positive, or zero.

(d) the value of the predicted Y Value is always negative.

2. In regression analysis, the input variable that is used to get a predicted value is

(a) the dependent variable.

(b) the independent variable.

(c) the least-squares variable.

(d) the random variable.

3. In the simple linear regression model with X Representing the independent variable and Y Representing the dependent variable, correlation analysis is used to

(a) find the least-squares regression line.

(b) find the slope of the regression line.

(c) measure the strength of the linear relationship between X And Y.

(d) draw a scatter plot.

4. If the correlation coefficient is zero, the slope of a linear regression line will be

(a) positive.

(b) negative.

(c) positive or negative.

(d) none of the above.

5. In the simple linear regression model, if there is a very strong correlation between the independent and dependent variables, then the correlation coefficient should be

(a) close to –1.

(b) close to +l.

(c) close to either –1 or +l.

(d) close to zero.

6. For the simple linear regression model, if all the points on a scatter plot lie on a straight line with correlation coefficient R = -1, then the slope of the regression line is

(a) –1.

(b) +l.

(c) positive.

(d) negative.

7. The least-squares equation for the line of best fit

(a) minimizes the error sum of squares.

(b) maximizes the error sum of squares.

(c) does not change the error sum of squares.

(d) does none of the above.

8. If through some analysis, one can conclude that the slope of the line of best fit is not equal to zero, then the simple linear regression model indicates that there is

(a) a positive relationship between the independent and dependent variables.

(b) a negative relationship between the independent and dependent variables.

(c) a positive or negative relationship between the independent and dependent variables.

(d) no relationship between the independent and dependent variables.

9. Which of the following is not a possible value of the correlation coefficient?

(a) +1

(b) -1

(c) 0.011

(d) 1.11

10. A negative correlation coefficient between the dependent variable Y And the independent variable X Indicates that

(a) large values of X Are associated with small values of Y.

(b) large values of X Are associated with large values of Y.

(c) small values of X Are associated with small values of Y.

(d) none of the above answers are correct.

11. For the simple linear regression model, if the unit for the dependent variable is square feet, then the unit for the independent variable

(a) must be square feet.

(b) can be some unit of square measurement.

(c) can be any unit.

(d) cannot be a unit of square measurement.

12. In simple linear regression analysis, there

(a) is only one independent variable in the model.

(b) could be several linear independent variables in the model.

(c) is only one nonlinear term in the model.

(d) is at least one nonlinear term in the model.

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