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2 years ago

Which of the following best describes the slope of the line below?

Mathematics

1 answer:

nikitadnepr [17]2 years ago

4 0

Hi, please link an image or describe so we can help!

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Rico bought 3 adult tickets and 5 child tickets for a total of $50.

aliina [53]

Step-by-step explanation:

3x + 5y = 50

x + 5y = 31

use substitution

x = 31-5y

3(31-5y) +5y = 50

93 -15y + 5y = 50

93 - 10y = 50

--10y = -43

y = 43/10 = $4.30 for kids

now solve for x

x + 5(4.30) = 31

x + 21.5 = 31

x = $9.5 for adults

4 0

2 years ago

Find and simplify the quotient 2/3 divided by 8/9

Anuta_ua [19.1K]

The answer is 3/4 and it was already simplified

8 0

3 years ago

I don't know this please help give brainlest

NARA [144]

Answer:

15x-9+y

Is required perimeter.

3 0

2 years ago

Read 2 more answers

Richard had his car repaired at a body shop.

Alisiya [41]

Answer:

2 hours

Step-by-step explanation:

308-100=208

208÷52=2

6 0

3 years ago

Determine whether a probability distribution is given. If a probability distribution is given, find its mean and standard deviat

drek231 [11]

Answer:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 0*0.031 +1*0.156+ 2*0.313+3*0.313+ 4*0.156+ 5*0.031 = 2.5$

We can find the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 0^2*0.031 +1^2*0.156+ 2^2*0.313+3^2*0.313+ 4^2*0.156+ 5^2*0.031 =7.496$

And we can calculate the variance with this formula:

$Var(X) =E(X^2) -[E(X)]^2 = 7.496 -(2.5)^2 = 1.246$

And the deviation is:

$Sd(X) = \sqrt{1.246}= 1.116$

Step-by-step explanation:

For this case we have the following probability distribution given:

X 0 1 2 3 4 5

P(X) 0.031 0.156 0.313 0.313 0.156 0.031

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).

We can verify that:

$\sum_{i=1}^n P(X_i) = 1$

And $P(X_i) \geq 0, \forall x_i$

So then we have a probability distribution

We can calculate the expected value with the following formula:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 0*0.031 +1*0.156+ 2*0.313+3*0.313+ 4*0.156+ 5*0.031 = 2.5$

We can find the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 0^2*0.031 +1^2*0.156+ 2^2*0.313+3^2*0.313+ 4^2*0.156+ 5^2*0.031 =7.496$

And we can calculate the variance with this formula:

$Var(X) =E(X^2) -[E(X)]^2 = 7.496 -(2.5)^2 = 1.246$

And the deviation is:

$Sd(X) = \sqrt{1.246}= 1.116$

6 0

3 years ago