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3 years ago

How would you do this last part?

Mathematics

1 answer:

alina1380 [7]3 years ago

8 0

Answer:

broken heart thats the last one lol

Step-by-step explanation:

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. (16/4) + (10-3)<br> Plzz I need an answer quickly. I really would appreciate it

musickatia [10]

Answer:

Explanation

(16/4)+(10-3)

4+(10-3)

4+7

4 0

3 years ago

Madison is baking party favors she wants to make enough favor so each guest gets the same number of favors she knows there will

iris [78.8K]

Answer:

It would be 24

Step-by-step explanation:

6: 6, 12, 18, 24

8: 8, 16, 24

The least common number is 24, so she should make at least 24.

4 0

3 years ago

Help please help me with this.

boyakko [2]

$\pi r^2h$

$\pi \times 7^2 \times 7$

$\pi \times 7^3$

$\displaystyle 343\pi$

3 0

3 years ago

Read 2 more answers

Solve for x. <br><br> 8x/7+9=30

kodGreya [7K]

X=18 (3/8)
(8x/7) +9 = 30
subtract 9 from both sides
8x/7=21
multiply 7 from both sides
8x=147
divide 8 from both sides and you get
x=18 (3/8)

6 0

3 years ago

Suppose that a college determines the following distribution for X = number of courses taken by a full-time student this semeste

lidiya [134]

Answer:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 3*0.07 +4*0.4 +5*0.25 +6*0.28= 4.74$ In order to find the variance we need to calculate first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 3^2*0.07 +4^2*0.4 +5^2*0.25 +6^2*0.28= 23.36$ And the variance is given by:

$Var(X) = E(X^2) +[E(X)]^2 = 23.36 -[4.74]^2 = 0.8924$

And the deviation would be:

$Sd(X) =\sqrt{0.8924} =0.9447$

Step-by-step explanation:

Previous concepts

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).

Solution to the problem

For this case we have the following distribution given:

X 3 4 5 6

P(X) 0.07 0.4 0.25 0.28

We can calculate the mean with the following formula:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 3*0.07 +4*0.4 +5*0.25 +6*0.28= 4.74$

In order to find the variance we need to calculate first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 3^2*0.07 +4^2*0.4 +5^2*0.25 +6^2*0.28= 23.36$

And the variance is given by:

$Var(X) = E(X^2) +[E(X)]^2 = 23.36 -[4.74]^2 = 0.8924$

And the deviation would be:

$Sd(X) =\sqrt{0.8924} =0.9447$

3 0

3 years ago