Back to Data. Imagine that someone takes many measurements of a real-world quantity at regular intervals of time, thereby producing a large data set S={x1,x2,,xN} consisting of the values of their measurements, ordered according to the times at which they were taken. After receiving this data, you produce the new data set S={y1,y2,,yN1}, where yn=xn+1xn for 1n0. Based on this finding, what kind of a function do you think will best fit the date? That is, what kind of a function do you think will best describes the values of the measurements xn in terms of the times at which they were taken? B. Suppose instead that you go on to compute S={z1,z2,,zN2}, where zn=yn+1yn for 1n0. Based on this finding, what kind of a function do you think will best fit the data? Back to Data. Imagine that someone takes many measurements of a real-world quantity at regular intervals of time, thereby producing a large data set S={x1,x2,,xN} consisting of the values of their measurements, ordered according to the times at which they were taken. After receiving this data, you produce the new data set S={y1,y2,,yN1}, where yn=xn+1xn for 1n0. Based on this finding, what kind of a function do you think will best fit the date? That is, what kind of a function do you think will best describes the values of the measurements xn in terms of the times at which they were taken? B. Suppose instead that you go on to compute S={z1,z2,,zN2}, where zn=yn+1yn for 1n0. Based on this finding, what kind of a function do you think will best fit the data<1><><1><>