Help asap 1) To which set of numbers does the number belong? Choose all the sets to which it belongs. -5.2

a)Natural

b)Whole

C)integer

d)rational

e)irrational

f)real

2)To which set of numbers does the number belong? Choose all the sets to which it belongs. -4

a)Natural

b)Whole

C)integer

d)rational

e)irrational

f)real

3) To which set of numbers does the number belong? Choose all the sets to which it belongs. -4.3212

a)Natural

b)Whole

C)integer

d)rational

e)irrational

f)real

4) To which set of numbers does the number belong? Choose all the sets to which it belongs. square root of 4

a)Natural

b)Whole

C)integer

d)rational

e)irrational

f)real

5) To which set of numbers does the number belong? Choose all the sets to which it belongs. square root of 7

a)Natural

b)Whole

C)integer

d)rational

e)irational

f)real

(1) d, f     (2) c, d, f     (3) e, f      (4) a, b, c, d, f     (5) e, f

Step-by-step explanation:

a) Natural Numbers:            1, 2, 3, ...

b) Whole Numbers:          0, 1, 2, 3, ...     (add zero to the Natural numbers)

c) Integers:   ..., -3, -2, -1, 0, 1, 2, 3, ...   (add negatives to the Whole numbers)

d) Rationals: Add terminating and repeating decimals to Integers.

************

e) Irrationals: Non-repeating decimals that are non-terminating.  This is its own category so cannot be a Rational number or above.

f) Real Numbers: ALL of the above (a - e) are Real numbers.

1) -5.2  has a terminating decimal so it is a RATIONAL number.

2) -4  is below zero so is an INTEGER which means it is also a RATIONAL #

3) -4.3212... is a non-terminating decimal so it is an IRRATIONAL number

4) = 2 is a NATURAL number which means it is also a WHOLE number, INTEGER, and RATIONAL number.

5)  is a non-terminating decimal so it is an IRRATIONAL number

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! )