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2 years ago

Pleaseeeeeeeeeeeeeeeeeeeeeeeeeeeeee

Mathematics

2 answers:

Anna [14]2 years ago

8 0

Answer:

180(n-2)

Step-by-step explanation:

that's to find interior angles

VashaNatasha [74]2 years ago

3 0

Answer:

180(n-2) is formula for finding interior angles if n is number of sides.

Step-by-step explanation:

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Jason has two bags with 6 tiles each.

dimaraw [331]

Answer:

1/4.

Step-by-step explanation:

I am assuming that there are 3 even and 3 odd tiles in each bag.

Probability( drawing an even tile form one bag) = 3/6 = 1/2.

The probability of drawing an even from the first and an even from the second = 1/2 * 1/2 = 1/4 (answer).

The individual probabilities are multiplied because the 2 events are independent.

8 0

3 years ago

Read 2 more answers

The revenue from selling xshirts is r(x) 15x The cost of buying x shirts is c(x) 7x + 20. The profit from selling xshirts is px)

timurjin [86]

The profit would be the difference between the total amount earned after selling each and every shirt and the costs of buying them so

p(x)= r(x)- c(x)

7x-20?

5 0

3 years ago

Read 2 more answers

Show the tens fact you used. Write the difference.

Mars2501 [29]

What exactly do you mean? Is there answer's to the problem or more to the problem?

7 0

3 years ago

Help please and thank you

aksik [14]

Remember
$(a^b)^c=a^{bc}$
and
$\frac{x^a}{x^b}=x^{a-b}$

so

$\frac{(7^2)^5}{7^{-6}}=$
$\frac{7^{2*5}}{7^{-6}}=$
$\frac{7^{10}}{7^{-6}}=$
$7^{10-(-6)}=$
$7^{10+6}=$
$7^{16}$

the answer is D

5 0

3 years ago

Please consider the following values for the variables X and Y. Treat each row as a pair of scores for the variables X and Y (wi

Studentka2010 [4]

Answer:

The Pearson's coefficient of correlation between the is 0.700.

Step-by-step explanation:

The correlation coefficient is a statistical degree that computes the strength of the linear relationship amid the relative movements of the two variables (i.e. dependent and independent).It ranges from -1 to +1.

The formula to compute correlation between two variables <em>X</em> and <em>Y</em> is:

$r(X, Y)=\frac{Cov(X, Y)}{\sqrt{V(X)\cdot V(Y)}}$