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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def linreg(x, y):
 """ does a linear regression """

    if len(x) != len(y):
        print('x and y must be same length')
        return
    xx, yy, xsum, ysum, xy, n, sum = 0, 0, 0, 0, 0, len(x), 0
    linpars = {}
    for i in range(n):
        xx += x[i] * x[i]
        yy += y[i] * y[i]
        xy += x[i] * y[i]
        xsum += x[i]
        ysum += y[i]
        xsig = np.sqrt(old_div((xx - old_div(xsum**2, n)), (n - 1.)))
        ysig = np.sqrt(old_div((yy - old_div(ysum**2, n)), (n - 1.)))
    linpars['slope'] = old_div(
        (xy - (xsum * ysum / n)), (xx - old_div((xsum**2), n)))
    linpars['b'] = old_div((ysum - linpars['slope'] * xsum), n)
    linpars['r'] = old_div((linpars['slope'] * xsig), ysig)
    for i in range(n):
        a = y[i] - linpars['b'] - linpars['slope'] * x[i]
        sum += a
    linpars['sigma'] = old_div(sum, (n - 2.))
    linpars['n'] = n
    return linpars