All categories

3 years ago

Pleaseeeee halpppp

Mathematics

2 answers:

jonny [76]3 years ago

7 0

The volume would be 36 9/16
(L•W•H)
hope this helps u have a nice day

storchak [24]3 years ago

5 0

Answer:

Number of boxes that will fit =2340

Step-by-step explanation:

The shipping box volume can be calculated by the formula V = Lxwxh ,where L ,w ,h are length ,width and height of the box.

The length of the shipping box = $3\frac{3}{4} =\frac{15}{4} ft.$

Width = 3 ft.

Height = $3\frac{1}{4} =\frac{13}{4} ft.$

Volume of shipping box = $\frac{15}{4} .3 .\frac{13}{4} =\frac{585}{16} = 36.6 ft$ .cubic ft.

Volume of shipping box can also be calculated by multiplying base area with the height of box.

Base area of box = $\frac{15}{4} .3=\frac{45}{4} square ft.$

Volume of box = base area x height = $\frac{45}{4} .\frac{13}{4} = 36.6 cubic ft.$

Volume of packing cubes = $\frac{1}{4} .\frac{1}{4} .\frac{1}{4} =\frac{1}{64}$ cubic ft.

Number of fish boxes that will fit in the shipping box = volume of shipping box ÷ volume of fish food box = 36.6 ÷ $\frac{1}{64}$ =2340 .

You might be interested in

The number of surface flaws in plastic panels used in the interior of automobiles has a Poisson distribution with a mean of 0.08

kvv77 [185]

Answer:

a) 44.93% probability that there are no surface flaws in an auto's interior

b) 0.03% probability that none of the 10 cars has any surface flaws

c) 0.44% probability that at most 1 car has any surface flaws

Step-by-step explanation:

To solve this question, we need to understand the Poisson and the binomial probability distributions.

Poisson distribution:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

$P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}$

In which

x is the number of sucesses

e = 2.71828 is the Euler number

$\mu$ is the mean in the given interval.

Binomial distribution:

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

$C_{n,x} = \frac{n!}{x!(n-x)!}$

And p is the probability of X happening.

Poisson distribution with a mean of 0.08 flaws per square foot of plastic panel. Assume an automobile interior contains 10 square feet of plastic panel.

So $\mu = 10*0.08 = 0.8$

(a) What is the probability that there are no surface flaws in an auto's interior?

Single car, so Poisson distribution. This is P(X = 0).

$P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}$

$P(X = 0) = \frac{e^{-0.8}*(0.8)^{0}}{(0)!} = 0.4493$

44.93% probability that there are no surface flaws in an auto's interior

(b) If 10 cars are sold to a rental company, what is the probability that none of the 10 cars has any surface flaws?

For each car, there is a $p = 0.4493$ probability of having no surface flaws. 10 cars, so n = 10. This is P(X = 10), binomial, since there are multiple cars and each of them has the same probability of not having a surface defect.