You are working for a company that developed a new drug which increases HDL cholesterol (the good cholesterol). A variety of dosages were given to participants during a trial, and the increases of HDL cholesterol were measured. This information is summarized in the following plot: Each point in the above plot represents a participant who was given a dosage of mg and had an HDL increase of mg/dL. This information is stored in the 2d numpy array trial_data. The -values are stored in the first row of trial_data (i.e. trial_data[0]) and the -values are stored in the second row of trial_data (i.e. trial_data[1]). You are now working with a physician to determine the right dosage for one of her patients. 1) In order to help your client, first find a vector such that is the least squares line for the above data. Store the vector as a 1D-numpy array in beta. 2) The physician wants to raise the HDL level by 33 mg/dL. What dosage do you recommend? Save this as dosage. Hint: Recall from lab the various ways to compute least squares solutions. Another function you might find helpful is numpy.linalg.lstsq, though the methods used in lab are sufficient