Given a model prediction ŷ = ƒ (x), where x is our input data (consisting of N data items) y is our true labels and ƒ is our model, which statement best matches our least squares cost function ΟΙ ΣΝ (3 - 0;) 2N ΣN |yi − ŷi | 2¹ IIÑ (yi — ŷ;)² (y₁ - £₁) ² II (3-9₁) ³ · ΣN (xi — ŷi)² ON

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Q: From the flowing population calculate 5. Range 6- Mean 7. Coefficient range 8- Standard deviation

A: 1) range is (-100,950) => 950+100=1050 2)mean is sum/total number of readings)  = 3630/80=45.375…

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A: P ( X < 1.25 ) = 0.09609375 E ( X ) = 1.65278 Var ( X ) = 0.06724452

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A: Given The answer is given below.

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A:

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A:

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A: The solution to the above question is:

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Q: Calculate T(n) for Question 1. Question 1:…

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A: Answer is given below-

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A: The answer is given below.

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A: The variance of a random variable x , with mean Ex=μ , is defined as V(x)=E[(x-μ)2]

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