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Use the following linear regression equation to answer the questions. X1 = 1.9 + 3.3x2 - 7.5X3 + 2.5X4 (a) Which variable is the response variable? O X 4 O X , O X 3 OX1 Which variables are the explanatory variables? (Select all that apply.) O x X3 V X2 V X4 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant *2 coefficient *3 coefficient 4 coefficient (c) If X2 = 10, X3 = 2, and x4 = 4, what is the predicted value for x1 ? (Use 1 decimal place.) d) Explain how each coefficient can be thought of as a "slope" under certain conditions. If we hold all explanatory variables as fixed constants, the intercept can be thought of as a "slope." O If we look at all coefficients together, each one can be thought of as a "slope." If we hold all other explanatory variables as fixed constants, then we can look at one coefficient as a "slope." O If we look at all coefficients together, the sum of them can be thought of as the overall "slope" of the regression line. Suppose x3 and x4 were held at fixed but arbitrary values and X2 increased by 1 unit. What would be the corresponding change in x]? Suppose X, increased by 2 units. What would be the expected change in x1? Suppose x2 decreased by 4 units. What would be the expected change in x]? (e) Suppose that n = 8 data points were used to construct the given regression equation and that the standard error for the coefficient of X2 is 0.321. Construct a 95% confidence interval for the coefficient of x2. (Use 2 decimal places.) lower limit upper limit (f) Using the information of part (e) and level of significance 1%, test the claim that the coefficient of x2 is different from zero. (Use 2 decimal places.) t critical + Conclusion O Reject the null hypothesis, there is sufficient evidence that B2 differs from 0. Reject the null hypothesis, there is in ufficient evidence that B 2 differs from 0. Fail to reject the null hypothesis, there is insufficient evidence that B2 differs from 0. O Fail to reject the null hypothesis, there is sufficient evidence that B2 differs from 0. Explain how the conclusion of this test would affect the regression equation. If we conclude that B2 is not different from 0 then we would remove x, from the model. If we conclude that B2 is not different from 0 then we would remove x4 from the model. If we conclude that B2 is not different from 0 then we would remove x3 from the model. If we conclude that B2 is not different from 0 then we would remove x2 from the model