According to a Niclsen survey, 92% of consumers around the world say that they trust recommendations from friends and family most, above all other forms of advertising. Suppose we took random samples of n = 100

consumers from this population and computed the proportion of consumers in each sample who trust

recommendations from friends and family most.

What will be the shape of the sampling distribution of the proportions of consumers who trust

recommendations from friends and family most?

Choose 1

Skewed to the left

©

Skewed to the right

Approximately normal

Uniform

Skewed to the Left

Step-by-step explanation:

We have a left-skewed sampling distribution because the population proportion is so extreme relative to the sample size that there are fewer than 101010 expected failures per sample.

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! )

answer is 67%

step-by-step explanation: