1. Dave Dumbledore is studying the test scores of students in an econometrics class. Only juniors and seniors are enrolled in this class. Dave wants to determine if, other things being equal, seniors have statistically significantly higher test scores than juniors do. Dave uses the following regression specification: T=bo + bị SENIOR, + b2 JUNIOR, + other variables + U, where T- student i's test score; SENIOR, = 1 if student i is a senior and 0 if not; JUNIOR, -1 if student i is a junior and 0 if not; U,- error term; and the other variables include grades in math courses and SAT scores. Dave looks at his computer output and exclaims, "This is crazy! The computer refuses to include the variable JUNIOR, and actually prints out a message saying that I have to drop it!" Is something wrong with Dave's computer... or is something wrong with Dave? Explain your answer. %3D %3!

Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?

Use the following information to answer the next question:Fred’s Frozen Creations has been contracted to train Utah’s synchronized ice sculpting team. They have identified two different independent variables (ice sculpting hours and number of ice blocks used in training) in two different equations to evaluate the cost of training. The results of the two regressions are as follows: (PLEASE REFER TO ATTACHED IMAGE) 20.) Assume Fred’s Frozen Creations chooses to use the number of ice blocks to estimate the cost of training. Construct a 90% confidence interval for the cost of training when the number of ice blocks used is estimated at 1,300. Assume 1,300 ice blocks is within the relevant range. (Round all calculations to the nearest dollar) a. ($223,240, $371,338)b. ($211,035, $383,543)c. ($216,475, $364,573)d. ($258,475, $336,103)e. ($207,844, $386,734)f. ($208,275, $386,303)g. ($297,027, $297,551)h. None of the above.