Question :

Many of the leading companies like Microsoft and Google are based on technologies developed within universities. A professor in the business school like to analyze university factors that enhance innovation. He collects data on 143 universities in 2008 for a regression where the response variable is the number of startups (Startups), which is used as a measure for innovation. The explanatory variables include the university's research expenditure in $ millions (Research), the number of patents issued (Patents), and the age of its technology transfer office in years (Duration). Use the file Startups excel sheet to answer the following questions:

a) Build a parsimonious linear regression model to forecast the number of Startups given the other variables (Research fund, number of patents, etc.)

b) Predict the number of startups for a university that: spent $120 million on research, issued 8 patents, and has had a technology transfer office for 20 years.

c) How much more research expenditure is needed for the university to have an additional predicted startup, with everything else being the same?

d) Calculate the correlation between the variables. Is there multicollinearity in the model, and what is its effect if it does exist?

Submission Format: Submit the answers using MS word and submit the Excel Spreadsheet used to build the model.

Startups 1 1 1 1 12 0 9 0 10 3 3 10 5 1 4 7 0 1 0 3 0 3 5 0 9 12 2 2 12 1 3 0 2 1 20 0 1 2 3 2 4 2 0 0 0 6 5 0 2 5 3 2 4 1 1 0 11 1 10 2 2 0 9 2 0 1 1 0 2 1 5 3 10 6 0 1 55 2 0 0 11 3 0 14 2 0 1 0 11 0 2 8 3 0 2 0 3 2 0 13 1 3 6 3 0 6 2 5 3 0 0 1 0 2 3 6 0 5 0 5 5 2 10 2 0 2 2 2 3 20 5 2 9 0 0 4 3 3 6 2 2 1 1

Research 145.5236 237.5212 146.9840 304.2250 343.4238 10.7120 26.3600 14.8700 229.2800 139.2837 302.6129 640.0000 668.2275 174.1091 102.2090 678.1842 13.2000 16.1920 30.7770 390.9652 43.2491 206.5418 79.8832 144.9570 536.4125 660.0815 404.6215 251.6740 1183.7680 819.2889 95.8786 18.4444 391.7670 19.4060 1319.0000 57.0852 134.2000 161.1623 356.7670 60.3560 210.9510 96.1506 296.3800 89.7920 120.3234 310.6990 366.1370 115.5130 56.7275 702.5635 25.9776 138.7592 279.8494 188.0560 717.2440 40.1469 495.0990 63.1974 784.3243 83.5624 323.4040 106.8504 694.2175 29.1348 150.3760 582.3650 404.6150 94.0318 151.0077 146.8751 49.5978 32.8460 65.3200 547.1974 115.5379 110.8750 4403.6620 108.0000 317.5155 211.3931 661.0000 161.3362 166.3700 483.7980 350.2990 211.7782 84.4900 81.5322 830.7790 293.5640 197.7970 242.9660 164.1230 43.2130 377.4180 66.8014 346.3693 435.2470 325.3000 875.7535 583.5240 54.7090 354.7636 342.6482 98.8208 197.6285 33.1258 619.6000 29.8081 31.8954 103.3000 158.9638 101.3423 667.3547 641.6260 361.6022 28.0793 185.1979 22.7420 298.5000 484.6000 246.3971 527.1413 197.2517 201.3230 153.4613 377.1696 66.6105 59.5830 273.0059 90.6422 257.6510 1026.7885 14.4730 148.2570 444.3325 148.6550 199.6359 942.0000 148.6864 140.8622 249.2100 154.3820

Patents 8 16 12 11 9 0 3 0 21 15 9 59 54 13 8 32 1 4 3 3 2 11 5 12 46 55 8 27 45 23 5 8 25 6 140 1 4 0 48 8 7 9 13 11 1 30 37 9 3 15 5 4 13 11 38 2 24 20 44 34 36 1 132 3 4 28 10 5 8 5 4 4 1 19 10 4 224 57 29 8 28 23 12 52 33 11 5 2 55 24 4 15 6 7 13 9 23 25 4 75 37 6 20 13 5 11 2 17 6 2 4 18 4 44 36 25 2 5 0 31 41 15 25 3 6 10 15 8 5 33 5 12 56 0 6 16 6 23 98 10 6 7 3

Duration 23 23 20 25 32 7 22 8 16 21 38 26 29 23 13 22 9 13 9 23 12 12 12 15 18 31 17 73 35 9 66 19 22 8 68 7 24 14 16 20 13 28 17 18 18 19 24 13 8 18 17 13 19 28 19 3 20 15 29 10 19 11 38 8 19 16 21 24 30 23 13 2 9 20 14 18 29 23 22 25 15 21 11 25 29 21 12 22 27 33 14 24 12 8 19 14 21 14 19 26 51 16 21 16 11 13 6 23 15 9 9 24 16 22 16 28 13 15 2 18 37 25 17 23 18 20 18 9 14 40 10 31 25 1 21 18 14 23 83 23 69 20 9