Math, Stats, Julia, Predictions, Linear Regression.
DataFrames, Distributions, Random, LinearAlgebra, Plots; pyplot() using StableRNGs; rng = StableRNG(100); # Libraries data = DataFrame(Y = rand(rng, 12), X = 1:12) # create data xVals, yVals, n = data.X, data.Y, size(data)[1] x=0 y=0 # initialize variables N = 10^6 alphaMin, alphaMax, betaMin,