In VB.Net, how to calculate Linear Regression and output results like the example shown, using the given formulas.

Results using 1-D array Output the best fit line: using 1-D array Slope: 4.383333 Y-intercept : 17.6 Correlation Coefficient:.9975255 Coeffient of Determination: e.9950572 Results using 2-D array Output the best fit line: using 2-D array Slope: 4.383333 Y-intercept : 17.6 Correlation Coefficient: .9975255 Coeffient of Determination: 0.9958572 Answer to part 3 Since the correlation coefficient is nearly one, using 1inear model to present these data is appropriate Application ends The velocity of an experimental automobile is measured at specified time intervals. There are nine pairs of data recorded in the following table: Time, t, s 0 5 10 1520 25 30 35 40 Velocity, V, m/s 24 33 62 77 105 123 151 170 188 y-mx+ b Formula to calculate the Correlation Coefficient: n(.x, y, )-(,)(.yi ) The square of the correlation coefficient, , Il is named Coefficient of the Determination: Coefficient of the Determination r2 Results using 1-D array Output the best fit line: using 1-D array Slope: 4.383333 Y-intercept : 17.6 Correlation Coefficient:.9975255 Coeffient of Determination: e.9950572 Results using 2-D array Output the best fit line: using 2-D array Slope: 4.383333 Y-intercept : 17.6 Correlation Coefficient: .9975255 Coeffient of Determination: 0.9958572 Answer to part 3 Since the correlation coefficient is nearly one, using 1inear model to present these data is appropriate Application ends The velocity of an experimental automobile is measured at specified time intervals. There are nine pairs of data recorded in the following table: Time, t, s 0 5 10 1520 25 30 35 40 Velocity, V, m/s 24 33 62 77 105 123 151 170 188 y-mx+ b Formula to calculate the Correlation Coefficient: n(.x, y, )-(,)(.yi ) The square of the correlation coefficient, , Il is named Coefficient of the Determination: Coefficient of the Determination r2