Multiple choices based on regression analysis.
1. A regression analysis between sales (Y in $1000) and advertising (X in dollars) resulted in the following equation = 30,000 + 4 X.The above equation implies that an
1. increase of $4 in advertising is associated with an increase of $4,000 in sales
2. increase of $1 in advertising is associated with an increase of $4 in sales
3. increase of $1 in advertising is associated with an increase of $34,000 in sales
4. increase of $1 in advertising is associated with an increase of $4,000 in sales
2. Regression analysis is a statistical procedure for developing a mathematical equation that describes how
1. one independent and one or more dependent variables are related
2. several independent and several dependent variables are related
3. One dependent and one or more independent variables are related
4. None of these alternatives is correct.
3. In a simple regression analysis (where Y is a dependent and X an independent variable), if the Y intercept is positive, then
1. there is a positive correlation between X and Y
2. if X is increased, Y must also increase
3. if Y is increased, X must also increase
4. None of these alternatives is correct
4. The equation that describes how the expected value of the dependent variable (y) is related to the independent variable (x) is called
1. the correlation model
2. the regression equation
3. correlation analysis
4. None of these alternatives is correct.
5. In regression analysis, the independent variable is
1. used to predict other independent variables
2. used to predict the dependent variable
3. called the intervening variable
4. the variable that is being predicted
6. Larger values of r2 imply that the observations are more closely grouped about the
1. average value of the independent variables
2. average value of the dependent variable
3. least squares line
4. origin
7. In a regression analysis, the error term ? is a random variable with a mean or expected value of
1. zero
2. one
3. any positive value
4. any value
8. Correlation analysis is used to determine
1. the equation of the regression line
2. the strength of the relationship between the dependent and the independent variables
3. a specific value of the dependent variable for a given value of the independent variable
4. None of these alternatives is correct.
9. Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained = 120 - 10 X. Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to
1. increase by 120 units
2. increase by 100 units
3. increase by 20 units
4. decease by 20 units
10. If the coefficient of correlation is 0.8, the percentage of variation in the dependent variable explained by the variation in the independent variable is
1. 0.80%
2. 80%
3. 0.64%
4. 64%