The raw data areY_i, x_i1, x_i2 for i = 1, ..., n. Let beta^_0, beta^_1, beta^_2

Question

The raw data areY_i, x_i1, x_i2 for i = 1, ..., n. Let beta^_0, beta^_1, beta^_2 be the least squares estimates when fitting a plane. Suppose the y variable has been rescaled to y* where y* = 10 y.Let beta^*_0, beta^*_1, beta^*_2 be the least squares estimates for the data y^8_i, x_i1, x_i2, I = 1, , n. Which of the following are correct? Possibly more than one item is correct. Beta^*_1 = beta^_1/10 Beta^*_0 = 10 beta^_0 Beta^*_0 = beta^_0/10 Beta^*_1 = 10 beta^_1 beta^*_2 = beta^_2/10 beta^*_2 = 10 beta^_2 None of the above

Explanation / Answer

B, D and F

The new weights( beta coefficients) will have 10 times the magnitude as the dependent variable is 10 times the old one.

Hence, each of the 3 beta coefficients will grow to 10 times.

Following this , B and D and F are the right options.

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