# The same media consultants decided to continue their investigation of the focal relationship between income and TV viewing habits. In order to confirm the existence of the focal relationship, they decided to control for immigration status by adding a variable measuring the number of each survey respondent's grandparents who were born outside the U.S. The researchers wonder if immigration background could influence both income and TV watching (but they hope this is not true, because it could invalidate the focal relationship). The researchers conduct a multivariate regression by adding a measure of number of grandparents born outside the U.S. to the regression equation presented in Equation 1 of Table 1. The results of the second regression equation are presented in Equation 2 of Table 1. ]]Table 1. OLS Regression Coefficients Representing Influence of Income and Control Variables on Number of Hours of TV Watched per Day     Equation 1 Equation 2 Equation 3 Annual Income of respondent (x 1000) -.116 (.003) -.115 (.004) -.063 (.103) Number of respondent's grandparents born outside US   -.067 (.123) -.048 (.254) Average weekly hours of employment     -.131 (.000)         Y-intercept (Constant) 8.69 8.07 10.32         R2 .034 .038 .070 (Significance level in parentheses) Equation 2 can also be written as:  Y^ = 8.07 -.115 (X) - .067 (Z1) Question 1. Explain why the researchers are controlling for this new variable measuring the number of grandparents born outside the U.S. Specifically, your answer should identify which of the two possible elaboration strategies is being used? Question 2. Why are the researchers adding this new variable to the equation? You should not reference any numbers from the equation in your answer to this question.

Question

The same media consultants decided to continue their investigation of the focal relationship between income and TV viewing habits. In order to confirm the existence of the focal relationship, they decided to control for immigration status by adding a variable measuring the number of each survey respondent's grandparents who were born outside the U.S. The researchers wonder if immigration background could influence both income and TV watching (but they hope this is not true, because it could invalidate the focal relationship). The researchers conduct a multivariate regression by adding a measure of number of grandparents born outside the U.S. to the regression equation presented in Equation 1 of Table 1. The results of the second regression equation are presented in Equation 2 of Table 1.

]]Table 1. OLS Regression Coefficients Representing Influence of Income and Control Variables on Number of Hours of TV Watched per Day

 Equation 1 Equation 2 Equation 3 Annual Income of respondent (x 1000) -.116 (.003) -.115 (.004) -.063 (.103) Number of respondent's grandparents born outside US -.067 (.123) -.048 (.254) Average weekly hours of employment -.131 (.000) Y-intercept (Constant) 8.69 8.07 10.32 R2 .034 .038 .070

(Significance level in parentheses)

Equation 2 can also be written as:  Y^ = 8.07 -.115 (X) - .067 (Z1)

Question 1. Explain why the researchers are controlling for this new variable measuring the number of grandparents born outside the U.S. Specifically, your answer should identify which of the two possible elaboration strategies is being used?

Question 2. Why are the researchers adding this new variable to the equation? You should not reference any numbers from the equation in your answer to this question.

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