Using the normal error regression model (2.1) in an engineering safety experiment, a researcher found for the first 10 cases that R^2 was zero. Is it possible that for the complete set of 30 cases R^2 will not be zero? Could R^2 not be zero for the first 10 cases, yet equal to zero for all 30 cases? Explain. normal error regression model: Yi = β0 + β1Xi + Єi

Marcus needs to rewrite f(x) = x2 + 6x + 4 in vertex form.

The box plot shows the number of raisins found in sample boxes from brand c and from brand d. each box weighs the same. what could you infer by comparing the range of the data for each brand? a) a box of raisins from either brand has about 28 raisins. b) the number of raisins in boxes from brand c varies more than boxes from brand d. c) the number of raisins in boxes from brand d varies more than boxes from brand c. d) the number of raisins in boxes from either brand varies about the same.

Look at this pattern ; 1,4,9, number 10000 belongs in this pattern . what’s the place of this number?