Question

Given (x1, y1), (x2, y2), ..., (xn, yn), the best fitting data to y=f(x) by least squares requires minimization of:

• A. Σ[yi - f(xi)]
• B. Σ|yi - f(xi)|
• C. Σ[yi - f(xi)]²
• D. Σ[yi]²=Σyi/n

Hint:

Remember that the least squares method focuses on minimizing squared differences for better performance.

Answer 1

The Correct Option is C

The least squares method minimizes the sum of squared differences between the actual values yi and the predicted values f(xi): ∑[yi − f(xi)]². This approach penalizes larger deviations more heavily and is widely used in regression and optimization problems.