A manufacturer claims that the mean amount of juice in its bottles is 16.1 ounces. A consumer advocacy group wants to perform a hypothesis test to determine whether the mean amount is actually less than this. The hypotheses are:

The null hypothesis is .

The alternate hypothesis is

Step-by-step explanation:

A manufacturer claims that the mean amount of juice in its bottles is 16.1 ounces.

This means that at the null hypothesis, we test if the mean amount of juice is of 16.1, as claimed, that is:

A consumer advocacy group wants to perform a hypothesis test to determine whether the mean amount is actually less than this.

This means that at the alternate hypothesis, we test if the mean amount of juice is less than the claimed mean of 16.1 ounces. So:

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! )

1/3

step-by-step explanation:

to find this, you can divide 12 by 4 which is 3 or you can multiply 4 until you reach 12 (4x3=12). both should give you 3, meaning theres three times less bananas than there are oranges.