Solving least square estimation with regression line intercept at (0,0)

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For an approximate regression line that passes through coordinates (0,0), solve the least square estimation and find $$w, w_{0} , w_{1}$$

$$w=\frac{\sum_{i=1}^n x_{i}y_{i}}{\sum_{i=1}^n x_{i}^2}$$

$$w_{0} = \bar{y} - w_{1}\bar{x}$$

$$w_{1}=\frac{\sum_{i=1}^n x_{i}y_{i}-n\bar{x}\bar{y}}{(\sum_{i=1}^n x_{i}^2-n\bar{x}^2)}$$

Can someone explain the thought process behind starting this problem and how to go about it? I think I'm confused about how to start the issue since I'm only given the intercept. Thank you.