1. Given a data set {(xi,y:)}}=1, where xi, Yi ER, we want to find a least squares line = B. + B1x to fit the data set with minimum squared residuals Ei=1(yi i)? . a. Show that: * [?=1 Xiyi - (E"=1 x;)(E?=1 yi) _ =1 Xiyi niy 29_1 x} (E?-1 x;) 2 1 x ni Where, b. Use Python to generate a synthetic data set: Yi = 10 + 2x; + Where, Xis are values evenly spaced between 1 and 10, i.e., 1