regression_line.rs

use std::io;
use std::process;

fn main() {
   //Step 0 - Collect data
    let x: [f64; 8] = [44.0, 46.0, 59.0, 67.0, 74.0, 85.0, 97.0, 43.0];
    let y: [f64; 8] = [1200.0, 2400.0, 3200.0, 3000.0, 5000.0, 4000.0, 6000.0, 6050.0]; 
    println!("Total profit per month");

    //Step 1 - Compute the average of X
    let mut xtotal: f64 = 0.0;
    let mut x_iter = 0;
    while x_iter != x.len() {
        xtotal = xtotal + x[x_iter];
        x_iter = x_iter+1;
    }
    let x_len = x.len().to_string().trim().parse::<f64>().unwrap();
    let xmean: f64 = xtotal/x_len;
    println!("The average of X = {}", xmean);

    //Step 2 - Compute the average of Y
    let mut ytotal: f64 = 0.0;
    let mut y_iter = 0;
    while y_iter != y.len() {
        ytotal = ytotal + y[y_iter];
        y_iter = y_iter+1;
    }
    let y_len = y.len().to_string().trim().parse::<f64>().unwrap();
    let ymean: f64 = ytotal/y_len;
    println!("The Average of Y = {}", ymean);

    //Compute and store more values for linear regression
    //namely x2, y2, and xy
    let mut yy: f64 = 0.0;
    let mut xy: f64 = 0.0;
    let mut xx: f64 = 0.0;
    x_iter = 0;
    while x_iter != x.len() {
        xy = xy+(x[x_iter]*y[x_iter]);
        xx = xx+(x[x_iter]*x[x_iter]);
        yy = yy+(y[x_iter]*y[x_iter]);
        x_iter = x_iter+1;
    }
    println!("Sigma value of yy = {}", yy);
    println!("Sigma value of xy = {}", xy);
    println!("Sigma value of xx = {}", xx);

    //Compute B in y = mx + b
    // y sum * x^2 - x sum * xy / num x * x2 - x sum * x sum
    let b: f64 = ((ytotal*xx)-(xtotal*xy))/((x_len*xx)-(xtotal*xtotal));
    println!("the y intercept is = {}", b);

    //Compute M in y = mx + b
    let m: f64 = ((x_len*xy)-(xtotal*ytotal))/((x_len*xx)-(xtotal*xtotal));
    println!("the slope is = {}", m);

  
}