Linear Regression
Random data points and their linear regression. Created with the following Sage (http://sagemath.org) commands: X = RealDistribution('uniform', [-20, 60]) Y = RealDistribution('gaussian', 1.5) f(x) = 3*x/20 + 5 xvals = [X.get_random_element() for _ in range(100)] data = [(x, f(x) + Y.get_random_element()) for x in xvals] m, b = var('m b') g(x) = m*x + b g(x) = g(x).subs(find_fit(data, g, solution_dict=True)) p = list_plot(data) + plot(g, (x, -20, 60), color='red') p.save('linear_regression.svg')
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