Factor the top and bottom. vertical asymptotes are the values for x that will make the denominator = 0. To find the horizontal asymptote when the powers of the numerator and denominator are the same, just divide to coefficients.
asymptotes are where the graph cant go, the graph will get closer and closer by never touch....see the attachment
Hi!
The equation of a circle is (x – h)² + (y – k)² = r², with (h, k) being the center, r being the radius, and x + y being left as just x and y.
If the smallest circle has a radius of 3 units, then the next one is 7 units (4 units greater), and then the second largest 11 units, and then the largest 15. That means, for r in our equation, we're going to put in 15.
So we get:
(x – h)² + (y – k)² = 15², or
(x – h)² + (y – k)² = 225
The center of our circle is at (-4, 3). That means h = -4 and k = 3 in our equation. So let's substitute that in.
(x – (-4))² + (y – 3)² = 225
(x + 4)² + (y - 3)² = 225 is our final equation.
Hope this helped!
Answer:
Step-by-step explanation:
I think option 4 is the correct answer
If <em>x</em> = 4.338338338…, then
1000<em>x</em> = 4338.338338338…
and subtracting <em>x</em> from this eliminate the trailing decimal.
1000<em>x</em> - <em>x</em> = 4338.338338338… - 4.338338338…
999<em>x</em> = 4334
<em>x</em> = 4334/999
Answer:
In order to calculate the expected value we can use the following formula:
And if we use the values obtained we got:
Step-by-step explanation:
Let X the random variable that represent the number of admisions at the universit, and we have this probability distribution given:
X 1060 1400 1620
P(X) 0.5 0.1 0.4
In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".
The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).
And the standard deviation of a random variable X is just the square root of the variance.
In order to calculate the expected value we can use the following formula:
And if we use the values obtained we got:
