Answer:
Step-by-step explanation:
13p⁵ + 6p - 12p² -(-9p - p² - 13p⁵) = 13p⁵ + 6p - 12p² + 9p + p² + 13p⁵
{Distribute (-1) to the second expression}
= <u>13p⁵ + 13p⁵</u> <u>-12p² + p²</u> <u>+ 6p + 9p</u>
{Combine like terms}
= 26p⁵ - 11p² + 15p
Answer:
The answer to this problem is 3
Step-by-step explanation:
Answer:
5
Step-by-step explanation:
The equation
is given in slope-intercept form. Slope-intercept form is a way of writing the equation of a line in the format
, such that the coefficient of the parameter (x) is the slope, and constant (b) is the y-intercept. What that essentially means is,

The slope of a line is its rate of change, and the y-intercept is where the graph of the line intersects the y-axis. One can apply this knowledge here by saying that, the equation
is given in the slope-intercept form, and the coefficient (
) equals (
), therefore the slope is (
).
Answer:(3x+4)(x+6)
Step-by-step explanation:
4x+18x=22x and 4×6=24
Answer:

Now we can calculate the second moment with the following formula:
And replacing we got:

And the variance is given by:

And replacing we got:
![Var(X) = 3.59 -[1.71]^2 = 0.6659](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%203.59%20-%5B1.71%5D%5E2%20%3D%200.6659)
And the standard deviation is just the square root of the variance:

Step-by-step explanation:
Previous concepts
For this case we define the random variable X =" how many children the couple will have" and we know the following distribution:
X 1 2 3
P(X) 0.52 0.250 0.230
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 can find the expected value with the following formula:

And replacing we got:

Now we can calculate the second moment with the following formula:
And replacing we got:

And the variance is given by:

And replacing we got:
![Var(X) = 3.59 -[1.71]^2 = 0.6659](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%203.59%20-%5B1.71%5D%5E2%20%3D%200.6659)
And the standard deviation is just the square root of the variance:
