An equivalent way of representing this, using the notation in class, is 91-.1 = 1.28 91-.05 = 1.65 91-.025 = 1.96 91-.01 = 2.33 91-.005 = 2.58 An analyst states an economic model in which the quantity of coffee (Q) demanded depends on price (P) and temperature (T) according to Q = Bot BIP + B 2I + E. Suppose an analyst has a random sample of n = 1, 000 observations (Qi, Pi, Ti). The analyst regresses Q on P and T and obtains the regression line Q = 3 + -6P +-5T. ( 1 ) (8) (3) Numbers in parentheses are standard errors. The analyst believes that assumptions MLR.1-MLR.4 hold. The analyst treats n = 1, 000 as a large enough sample to apply the central limit theorem. i. The analyst believes an increase in T by 1 degree decreases Q by two units, all else equal. State this as a null hypothesis in terms of parameters.iv. Consider the hypotheses Ho : B1 = -1 Ha : B1 #-1. Test the null hypothesis at the a = .05 level. Please show your work and use the numbers provided in the problem. v. The analyst thinks there may be a coding error in the standard error for the coefficient in front of price. The reported number 8 is too low, but the analyst does not know by how much (so the correct standard error is above 8 and that's all we know). Based on this information, can you test the hypothesis described in part (ii)? If so, say yes and determine whether to reject or fail to reject. If not, say not enough information. vi. Suppose instead that the reported standard error 8 was too high (so the correct standard error was below 8 and that's all we know). Based on this information, can you test the hypothesis described in part (ii)? If so, say yes and determine whetehr to reject or fail to reject. If not, say not enough information