I must write a C program that meets the following requirements:

1. Data Entry Step: reads N ordered pairs of data (xi,yi) into a pair of arrays x[] and y[]. Query the user for a value for N in advance; N will not be greater than 100.

2. Analysis Step: using the obtained data and the formulas above, calculates the parameters m and b of the least-squares fit to the data and prints those values to the screen in an appropriate way.

3. Predictive Step: reads in a series of x values (number not known in advance, but no more than 100 values) until the user enters the sentinel value -999. Then (after all values are input) the program prints out a table of values for the least-fit line y=mx+b in two tab-separated columns labeled x and y, and computes and prints out the centroid the half-way point on the line segment between the extreme points on the line segment entered.

Linear Least-Squares is an attempt to find a straight line that best represents a set of data points. It is a very common problem in modeling and statistics you have a large set of observed data points, and you want to be able to describe it with a single line that fits the data as well as possible.