Least squares regression to find coefficients

Not sure what to do here. I tried doing it all seperately by setting noise to 0, then to 50, then 100 and using polyfit but I get the same answer everytime. I also tried using the backslash.

y(𝑥)=𝑝1+𝑝2𝑥

where

x = 0:0.1:20;

noise =?? % a number, to define

y= 4*x + noise*rand(1,length(x));

Vary the value for noise as 0, 50 and 100 to get three different results for 𝑝1and 𝑝2,

From a linear algebra standpoint, determine the coefficients, 𝑝1and 𝑝2, of the least-squares-regression of a line fit through the data defined above.

Answer 1

[Asad (Mehrzad) Khoddam]

one solution is:

[length(x) sum(x); sum(x) sum(x.^2)]\[sum(y) ; sum(x.*y)]