Linear Regression in Matrix-Vector Form) An ECE student John is doing an elec- tronic circuits lab during which he needs to determine the conductance of a resistor using a voltage meter, a current meter, and a DC power source. The voltage meter is connected in parallel with the resistor and the current meter is in series with the resistor. Both meters are analog devices so the readings recorded by John have errors. The power source is tunable and has a range of 1 to 5 V. Each time John will try a uniformly random input voltage level and record the readings of both voltage and current meters. Denote the voltage reading as xi and the current reading as yi for the ith measurement. Assume the true conductance G = 2 m1. a) Using a linear model yi = Gxi ei, where ei is a zero-mean noise with standard deviation e = 0.1 mA, simulate a dataset of n = 10 measurements. [Hint: You may use Matlab command rand() to generate a uniformly random value in [0, 1] and 0.1*randn() to generate a zero-mean Gaussian noise with standard deviation 0.1. Throughout this problem, you may ignore the units such as m1