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2. Suppose Y is related to R and S in the following nonlinear way: Y = aR'S a. In order to estimate the parameters a, b, and c, the equation must be trans- formed into the form: Twenty-six observations are used to obtain the following regression results: DEPENDENT VARIABLE: LNY R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 26 0.3647 4.21 0.0170 PARAMETER STANDARD VARIABLE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 2.9957 0.3545 8.45 0.0001 LNR 2.34 2.69 0.0134 LNS 0.687 0.334 2.06 0.0517 b. There are degrees of freedom for the f-test. At the 1% level of significance, the critical /-value for the test is C. At the 1% level of significance, a (is, is not) significant, b (is, is not) significant, and e (is, is not) signifi- cant. d. The estimated value of a is e. The p-value for b indicates that the exact level of significance ise. The p-value for b indicates that the exact level of significance is percent, which is the probability of f. At the 1% level of significance, the critical value of the F-statistic is The model as a whole (is, is not) significant at the 1% level. g. If R = 12 and S= 30, the fitted (or predicted) value of Y is h The percentage of the total variation in the dependent variable nor explained by the regression is percent. If R increases by 14%, Y will increase by percent. A 6.87% increase in Y will occur if S (increases, de- creases) by percent