1. x -    4
x - 6|x² - 10x + 24
- (x² - 6x)
-4x + 24
- (4x + 24)
0
The answer is C.

2. A. 9x² + 12x - 3
3(x²) + 3(4x) - 3(1)
3(x² + 4x - 1)

B. 9x² + 3x - 5
Not Factored

C. 6x² + 10x - 4
2(3x²) + 2(5x) - 2(2)
2(3x² + 5x - 2)
2(3x² + 6x - x - 2)
  2(3x(x) + 3x(2) - 1(x) - 1(2))
  2(3x(x + 2) - 1(x + 2))
  2(3x - 1)(x + 2)

D. 6x² + 7x - 6
Not Factored

The answer is C.

3. 3x³ - 4x² + 3x - 6
x + 2|3x⁴ + 2x³ - 5x² + 0x - 4
- (3x⁴ + 6x³)
-4x³ - 5x²
- (-4x³ - 8x²)
3x² + 0x
  - (3x² + 6x)
-6x - 4
  - (-6x - 12)
8
The answer is A.

7 0

3 years ago

Find the product <br> -1/2y(2y^3-8)

blondinia [14]

Answer:

-y^4+4y

Step-by-step explanation:

3 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

The graph shows the relationship between the radius and volume for many cones whose height is 6imches

borishaifa [10]

Answer:

the 3rd one

Step-by-step explanation:

6 0

3 years ago

Read 2 more answers