Catherine chao, director of marketing research, is evaluating consumer acceptance of a new toothpaste package. her staff reports that 17% of a random sample of 200 households prefers the new package to all other package designs. if catherine concludes that 17% of all households prefer the new package, she is using ) a point estimateb) a range estimatec) a statistical parameterd) an interval estimatee) an exact estimate

(a) = a point estimate

Step-by-step explanation:

In point estimation, a single sample statistic is calculated from the sample to provide a best estimate of the true value of the corresponding population parameter. That single relevant statistic is called point estimator and the value of the statistic is called point estimate. In this case, the 17% of a random sample of 200 households that prefers the new package to all other package designs according to the report is a point estimate of the percentage of all households that prefer the new package. Thus, until the next sample of items is drawn and examined, Catherine can actually conclude that 17% of all households prefer the new package.

the answer   is 200

step-by-step explanation:

this is a problem about poisson probabilities.   i don't know if you've

already studied poisson distributions, or if you have a place to look

to read more about the subject.  

here's how you can see a poisson distribution coming.   when there are

a lot of events that may happen at any time (or any place), and when

you're counting how many of them happen at a particular time (or a

particular place), and each event is independent of the others, then

the result is a poisson distribution.   this is roughly true for the

chocolate chips; one chip being in a cookie has only a small effect on

the probability that another chip will be in the cookie.

once you know you have a poisson distribution, you know a lot.   there

is only one parameter to a poisson distribution, so if you know the

mean, you know everything.   the form of the distribution is

  probability of n chips = {[e^(-x)]*(x^n)} / (n! )