If the regression parameters $\beta _ { 0 }$ and $\beta _ { 1 }$ are estimated by minimizing the expression $f _ {w } \left( b _ { 0 } , b _ { 1 } \right) = \sum w _ { i } \left[ y _ { i } - \left( b _ { 0 } + b _ { 1 } x _ { i } \right) \right] ^ { 2 }$ , where the $w _ { i }$ 's are weights that decrease with increasing $x _ { i }$ , this yields____________estimates.

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The Answer of If the regression parameters $\beta _ { 0 }$ and $\beta _ { 1 }$ are estimated by minimizing the expression $f _ {w } \left( b _ { 0 } , b _ { 1 } \right) = \sum w _ { i } \left[ y _ { i } - \left( b _ { 0 } + b _ { 1 } x _ { i } \right) \right] ^ { 2 }$ , where the $w _ { i }$ 's are weights that decrease with increasing $x _ { i }$ , this yields____________estimates.

If the Regression Parameters β0\beta _ { 0 }β0​ And β1\beta _ { 1 }β1​

If the Regression Parameters $\beta _ { 0 }$ And $\beta _ { 1 }$