Consider data x1, . . , xn and y1, . . , yn. say that we have the regression model yi = θxi + εi , where the εis are independent and identically distributed normal random variables with mean 0 and variance σ 2 . assume that x1, . . , xn are not random. a) find the maximum likelihood estimate for θ. b) what is the mean squared error for your estimate ˆθ? it will depend on θ and σ 2 as well as x1, . . , xn.

Mercury poisoning is dangerous overload of mercury within the body. a major source of mercury within the body, a major source of mercury poisoning is consuming fish that contain mercury. certain fish are more prone to having higher levels of mercury than others. the pie chart shows the distribution of four breeds of fish at a hatchery. the hatchery has approximately 6,000 fish. a biologist from the centers for disease control and prevention randomly test 5% of each breed of fish for mercury content. her findings are shown in the following table. based on the biologist's findings, if a single salmon is randomly selected from those that were tested, what is the probability that this particular fish would have a dangerous mercury level? a) 0.001 b) 0.004 c) 0.02 d) 0.08

I'm terrible at math any here is appreciated.

One positive number is 9 more than twice another. if their product is 95, find the numbers