Let Y denote a Bernoulli(θ) random variable with 0 < θ < 1. Suppose we are interested in estimating the odds ratio, γ = θ/(1 − θ), which is the probability of success over the probability of failure. Given a random sample {Y1,...,Yn}, we know that an unbiased and consistent estimator of θ is Y¯, the proportion of successes in n trials. A natural estimator of γ is G = Y¯ /(1−Y¯), the proportion of successes over the proportion of failures in the sample

a. Why is G not an unbiased estimator of γ (show this matematically and explain)?
b. Use the properties of plim (mathmatically) to show that G or Y/(1-Y) is a consistent estimator of γ.

i really dont know

step-by-step explanation:

y + 11 = (1/4)(x + 16)

step-by-step explanation:

the correct option is:

b. a value of the variable that makes the polynomial equal to zero.

the root or roots of a polynomial are the values of the variable that makes the polynomial equal to 0. we can find the roots of a polynomial making the expression equal to 0 and then, isolating the variable (it it has just one variable).

for example, given the following polynomial:

the root or zero of the polynomial, can be found by making the expression equal to 0, and then, isolating the variable, so, finding the root we have:

therefore, we have that the root of the polynomial is equal to 2.

we must remember that the number of roots that a polynomial can have, will depend on the degree of the polynomial, a first degree polynomial have will have one single root, a second degree polynomial (quadratic expression) may have two roots and so.

hence the correct option is:

b. a value of the variable that makes the polynomial equal to zero.

have a nice day!

sina-sinb

cosb+cosa

tana-tanb

cos0+cos x pi/3

20tan

step-by-step explanation: