Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 79.7 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.3 per 10 million people? a. Find the equation of the regression line. y with caret equals(Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) b. The best predicted number of Nobel Laureates when the number of internet users per 100 is79.7 is (Round to one decimal place as needed.) ### Internet Users and Nobel Laureates DataThis table showcases the correlation between the number of Internet users per 100 people and the number of Nobel Laureates in different regions or countries. | Internet Users Per 100 | Nobel Laureates ||------------------------|-----------------|| 79.8 | 5.5 || 79.3 | 24.4 || 78.7 | 8.5 || 45 | 0.1 || 82.2 | 6.1 || 38 | 0.1 || 89.8 | 25.2 || 88.9 | 7.5 || 79.1 | 9 || 83.5 | 12.7 || 52.6 | 1.9 || 76.9 | 12.8 || 57.1 | 3.3 || 78.7 | 1.5 || 92.5 | 11.4 || 94.6 | 25.3 || 64.4 | 3.1 || 57.4 | 1.9 || 67.6 | 1.7 || 94.4 | 32.1 || 85.6 | 31.7 || 85.9 | 19 || 77.9 | 10.7 |#### Analysis:This data can be used to explore potential relationships between the density of Internet connectivity and educational or research achievements, exemplified by the number of Nobel Laureates. You can observe that higher numbers of Internet users do not always correlate directly with a higher number of Nobel Laureates, suggesting that while connectivity may play a significant role in facilitating education and research, other factors are also influential.

from the given information we make the following table to compute regression equation x y x2 y2 xy 79.8 5.5 6368.04 30.25 438.9 79.3 24.4 6288.49 595.36 1934.92 78.7 8.5 6193.69 72.25 668.95 45 0.1 2025 0.01 4.5 82.2 6.1 6756.84 37.21 501.42 38 0.1 1444 0.01 3.8 89.8 25.2 8064.04 635.04 2262.96 88.9 7.5 7903.21 56.25 666.75 79.1 9 6256.81 81 711.9 83.5 12.7 6972.25 161.29 1060.45 52.6 1.9 2766.76 3.61 99.94 76.9 12.8 5913.61 163.84 984.32 57.1 3.3 3260.41 10.89 188.43 78.7 1.5 6193.69 2.25 118.05 92.5 11.4 8556.25 129.96 1054.5 94.6 25.3 8949.16 640.09 2393.38 64.4 3.1 4147.36 9.61 199.64 57.4 1.9 3294.76 3.61 109.06 67.6 1.7 4569.76 2.89 114.92 94.4 32.1 8911.36 1030.41 3030.24 85.6 31.7 7327.36 1004.89 2713.52 85.9 19 7378.81 361 1632.1 77.9 10.7 6068.41 114.49 833.53 ∑x = 1729.9 ∑y = 255.5 ∑x2 = 135610.07 ∑y2 = 5146.21 ∑xy = 21726.18