I have done the regression in Excel but for the Intercept row I get #N/A. Is that normal? The Excel has 260 observations (I uploaded the first rows as an example). I also uploaded the regression. And please answer Questions 3 and 4. Thank you so much.

2. A number of regional economists suggest that a labor force with a higher share of college graduates sets the base for a more successful metropolitan area. Using the data associated with this problem set on Blackboard, regress the per capita personal income by metropolitan area on the share of the adult population that has a college degree or higher by metropolitan area. Present a table with your results.

3. Use excel to graph the basic data and the estimated regression line from (2). Write a short paragraph interpreting those findings, their significance and their limitations.

4. Using the equation you estimated in (2) what would you predict would be the increase in per capita personal income in Chicago if the share of the adult population with a college degree increased by five percentage points? Explain.

A B C D m F G H 1 SUMMARY OUTPUT 2 3 Regression Statistics 4 Multiple R 0.984260052 5 R Square 0.96876785 6 Adjusted R Sql 0.964906846 7 Standard Erro 4875.23441 8 Observations 260 9 10 ANOVA 11 df SS MS F Significance F 12 Regression 1 1.90945E+11 1.90945E+11 8033.736749 1.9778E-196 13 Residual 259 6155888834 23767910.56 14 Total 260 1.97101E+11 15 16 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 17 Intercept 0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A 18 college or hig 132239.28 1475.372477 89.63111485 5.6579E-197 129334.0273 135144.5326 129334.0273 135144.5326 19A B C D E Total Metropolitan Per Capita college or Metropolitan Statistical Area Population Personal Income Income higher share Akron, OH 697558 19,460,700,000 27,898 0.215 W N Albany-Schenectady-Troy, NY 839570 27,631,400,000 $ 32,911 0.256 4 Albuquerque, NM 877676 22,493,500,000 25,628 0.213 5 Allentown-Bethlehem-Easton, PA-NJ 820490 24,872,100,000 30,314 0.193 Amarillo, TX 246399 6,480,477,636 $ 26,301 0.154 7 Anchorage, AK 447361 15,447,300,000 $ 34,530 0.197 8 Ann Arbor, MI 353632 12,412,500,000 un t 35,100 0.363 9 Anniston-Oxford-Jacksonville, AL 114315 2,577,476,393 $ 22,547 0.138 10 Asheville, NC 499767 12,897,500,000 $ 25,807 0.242 11 Atlanta-Sandy Springs-Roswell, GA 5516118 160,670,000,000 29,127 0.243 12 Atlantic City-Hammonton, NJ 262404 7,432,307,504 $ 28,324 0.173 13 Auburn-Opelika, AL 151617 3,776,440,482 $ 24,908 0.214 14 Augusta-Richmond County, GA-SC 525394 12,750,000,000 24,268 0.188 15 Austin-Round Rock, TX 1962613 63,812,600,000 $ 32,514 0.281 16 Bakersfield, CA 862323 17,882,300,000 $ 20,737 0.102 17 Baltimore-Columbia-Towson, MD 2708542 96,111,800,000 35,485 0.268 18 Bangor, ME 152037 3,741,095,743 24,606 0.206 19 Barnstable Town, MA 241101 9,657,055,990 $ 40,054 0.362 20 Baton Rouge, LA 818158 21,777,700,000 26,618 0.183 21 Beaumont-Port Arthur, TX 386729 9,180,489,824 $ 23,739 0.118 22 Bellingham, WA 206010 5,748,075,493 27,902 0.222 23 Bend-Redmond, OR 167578 4,765,019,873 $ 28,435 0.231 24 Binghamton, NY 229151 6,116,791,993 $ 26,693 0.213 25 Birmingham-Hoover, AL 1113340 29,365,400,000 S 26,376 0.200 26 Bism ND 129555 1 370 744 635 33 737 0 240