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3 years ago

The rartio of cookies to milk is 3:1 .if there are 25 glasseees of milk how many cookies are there

Mathematics

2 answers:

nevsk [136]3 years ago

6 0

Answer:

Step-by-step explanation:

the ratio of cookies to milk is 3:1

so 25 * 3 = 75

hope this helps :)

Masja [62]3 years ago

5 0

Answer:

The answer is 75 cookies.

Step-by-step explanation:

Since the ratio of cookies to milk is 3:1, multiply 25 by 3 to get 75. The ratio is 75:25, which can be simplified to 3:1.

I hope this helped! :-)

You might be interested in

What is f(4) for the function f(x) = 7x + 6?<br> Please help asap

Black_prince [1.1K]

Answer:

f(4) for the function $f(x) = 7x + 6$ is $\mathbf{f(4)=34}$

Step-by-step explanation:

We need to find f(4) for the function $f(x) = 7x + 6$

For finding f(4) we will put x= 4 in the given function

$f(x) = 7x + 6$

Put x = 4

$f(4)=7(4)+6\\f(4)=28+6\\f(4)=34$

SO, f(4) for the function $f(x) = 7x + 6$ is $\mathbf{f(4)=34}$

4 0

3 years ago

Evaluate C(20, 2).<br> 380<br> 190<br> Or 18

wolverine [178]

The correct answer is 190

4 0

3 years ago

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.