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2 years ago

Which statement is true based on the diagram?

Mathematics

2 answers:

Margarita [4]2 years ago

6 0

Answer:

option B

Step-by-step explanation:

Triangle RST~ TRIANGLE RQP

andrew11 [14]2 years ago

5 0

The answer is the second bubble

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Cristina has completed .4 of his test. The test has 40 questions total. if he completes 12 more how many more will he have left?

katrin [286]

4 + 12 = 16

40 - 16

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3 years ago

A graph of quadratic function y = f(x) is shown below.

umka21 [38]

Answer:

{f|0 ≤ f(x)}; x² - 4x + 5

Step-by-step explanation:

To find the Quadratic Equation, plug the vertex into the Vertex Equation FIRST, y = a(x - h)² + k, where (h, k) → (2, 1) is the vertex, plus, -h gives you the OPPOSITE terms of what they really are, and k gives you the EXACT terms of what they really are: (x - 2)² + 1. Doing this will give you the Quadratic Equation of x² - 4x + 5. You understand now?

I am joyous to assist you anytime.

7 0

3 years ago

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6n+7n whats the answer

sergeinik [125]

13n

ahaha , it’s that easy !!

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2 years ago

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Multiply. Write your answer as a fraction in simplest form. 2/15 x 9

Mkey [24]

Answer:

6 /5

Step-by-step explanation:

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2 years ago

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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