least-squares-regression

I need help understing what to do here,

I know i need to slobe for p1 and p2x but stuck, I have the code below but just stuck.

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.

thank you

Answer 1

[KSSV]

Read about polyfit. If you have the data x, y you can fit a line and get p1, p2 using polyfit.

p = polyfit(x,y,1) ; 
p1 = p(1) ; p2 = p(2) ;