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3 years ago

Which of the following is the mathematical representation of Boyle's law?

1 answer:

3 0

The mathematical representation of Boyle's law is P1V1 = P2V2. The answer to your question is C. I hope that this is the answer that you were looking for and it has helped you.

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Marcus boxers dog 3/5 of a mile every day how far does Marcus walk his dog 6 days

lina2011 [118]

Marcus walks 3.5 miles

6 0

3 years ago

a container of coffee is 1/6 full.The container contains 2/3 of a pound of coffee.write division expression that represents the

zimovet [89]

Answer:

capacity of the container is 4 pound

Step-by-step explanation:

We have given that a container of the coffee is $\frac{1}{6}$ full

And it contains $\frac{2}{3}$ of a pound so $\frac{2}{3}$ pound

It means $\frac{1}{6}$ f of container contain $\frac{2}{3}$ pound coffee

So capacity of the container is $\frac{\frac{2}{3}}{\frac{1}{6}}=4pound$

So capacity of the container is 4 pound

8 0

3 years ago

Write in full text, no files plz.

slava [35]

Answer:

108 student tickets, and 176 adult tickets were sold.

I hope I helped, and thanks for the points!

Step-by-step explanation:

7 0

2 years ago

Binomial (x - 6) and trinomial (-2x2 + x + 9) are the factors of which of the

djyliett [7]

Answer:

Option (3)

Step-by-step explanation:

If binomial (x - 6) and trinomial (-2x² + x + 9) are the factors of a polynomial then their multiplication will be equal to the polynomial.

(x - 6)(-2x² + x + 9) = x(-2x² + x + 9) - 6(-2x² + x + 9)

= -2x³ + x² + 9x + 12x² - 6x - 54

= -2x³ + 13x² + 3x - 54

Therefore, Option (3) will be the correct option.

8 0

3 years ago

Fill in the blanks below to make a true statement. In a binomial experiment with n trials and probability of success p, if np (1

Sergeu [11.5K]

Answer:

$\mu_{x}=np$

$\sigma^2_{X}=np(1-p)$

Step-by-step explanation:

∵ When x is a random variable having distribution B(n, p), then for sufficiently large value of n, the following random variable has a standard normal distribution,

$\frac{x-\mu}{\sigma}\sim N(0,1)$