Multiple Choice Questions: The error term in simple regression represents: the difference between the estimated regression line and the population...

Multiple Choice Questions:

1. The error term in simple regression represents:

a. the difference between the estimated regression line and the population line.

b. the vertical distance from any point to the mean value of Y's.

c. the vertical distance from any point to the population regression line.

d. the vertical distance from any point to the estimated regression line.

e. none of the above.

2. In a multiple regression problem involving two quantitative independent variables, if β1 is computed to be ‑2, it means that

           a.  the relationship between x1 and y is significant.

           b.  y decreases by 2 units for each increase of one unit of x1, holding x2 constant.

           c.  the value of y is ‑2 when x1 equals zero.

           d.  none of the above.

3. The coefficient of multiple determination

           a.  measures the variation around the predicted regression equation.

           b.  measures the proportion of the variation in y that is explained by all the

                 independent variables in the model.

           c.  measures the proportion of the variation in y that is explained by x1 holding x2

                          constant.

           d. will have the same sign as β1.

4. If we want to add the independent variable, gender, to our existing model, how many variables are needed to represent its two levels,

           a. 1                                                     b. 2

           c. 4                                                     d. need more information

           e. none of the above

5. The graph of a model with one qualitative independent variable with three levels is

           a. three lines                                       b. three nonlinear functions

           c. two parallel lines                            d. a bar chart

           e. cannot be graphed

6. The least squares method guarantees that the

a.  sum of absolute deviations between each observation and the model is least compared  to any other model

b. sum of the deviations between each observation and the mean is zero

c. sum of squared deviations between each observation and the model is minimum compared to any other model

d. all of the above

e. none of the above