The tangent of x is defined to be its sine divided by its cosine: tan x = sin x cos x . The cotangent of x is defined to be the cosine of x divided by the sine of x: cot x = cos x sin x .
Answer:
7
Step-by-step explanation:
First ignore the cut corner and pretend that it is just a rectangle.
The rectangle's area would be 2×4=8.
Then find out the cut corner's area.
The area of that triangle would be 1.
8-1=7 So the area of the shape is 7.
Answer:
990 ways
Step-by-step explanation:
The total number of automobiles we have is 11.
Now, what this means is that for the first position , we shall be selecting 1 out of 11 automobiles, this can be done in 11 ways( 11C1 = 11!/(11-1)!1! = 11!/10!1! = 11 ways)
For the second position, since we have the first position already, the number of ways we can select the second position is selecting 1 out of available 10 and that can be done in 10 ways(10C1 ways = 10!9!1! = 10 ways)
For the third position, we have 9 automobiles and we want to select 1, this can be done in 9 ways(9C1 ways = 9!/8!1! = 9 ways)
Thus, the total number of ways the first three finishers come in = 11 * 10 * 9 = 990 ways
The sum of the 5 terms in the arithmetic series is 40.
Step-by-step explanation:
Step 1; First we need to determine the three values between a1= -14 and a5=30. The difference between the first and fifth value = 30 - (-14) = 30 + 14 = 44.
Since there are 4 values after a1 we divide the difference by the number of terms, the difference between each term = 44 / 4 = 11. So the difference between each term is 11.
Step 2; To find out the terms we just add the difference to the previous number.
a1 = -14.
a2 = -14 + 11 = -3.
a3 = -3 + 11 = 8.
a4 = 8 + 11 = 19.
a5 = 19 + 11 = 30.
So a1 + a2 + a3 + a4 + a5 = -14 -3 + 8 + 19 + 30 = 40.
Answer:
![l'(\theta) = \frac{1}{\sigma^2} \sum_{i=1}^n (X_i -\theta)](https://tex.z-dn.net/?f=%20l%27%28%5Ctheta%29%20%3D%20%5Cfrac%7B1%7D%7B%5Csigma%5E2%7D%20%5Csum_%7Bi%3D1%7D%5En%20%28X_i%20-%5Ctheta%29)
And then the maximum occurs when
, and that is only satisfied if and only if:
![\hat \theta = \bar X](https://tex.z-dn.net/?f=%20%5Chat%20%5Ctheta%20%3D%20%5Cbar%20X)
Step-by-step explanation:
For this case we have a random sample
where
where
is fixed. And we want to show that the maximum likehood estimator for
.
The first step is obtain the probability distribution function for the random variable X. For this case each
have the following density function:
![f(x_i | \theta,\sigma^2) = \frac{1}{\sqrt{2\pi}\sigma} exp^{-\frac{(x-\theta)^2}{2\sigma^2}} , -\infty \leq x \leq \infty](https://tex.z-dn.net/?f=%20f%28x_i%20%7C%20%5Ctheta%2C%5Csigma%5E2%29%20%3D%20%5Cfrac%7B1%7D%7B%5Csqrt%7B2%5Cpi%7D%5Csigma%7D%20exp%5E%7B-%5Cfrac%7B%28x-%5Ctheta%29%5E2%7D%7B2%5Csigma%5E2%7D%7D%20%2C%20-%5Cinfty%20%5Cleq%20x%20%5Cleq%20%5Cinfty)
The likehood function is given by:
![L(\theta) = \prod_{i=1}^n f(x_i)](https://tex.z-dn.net/?f=%20L%28%5Ctheta%29%20%3D%20%5Cprod_%7Bi%3D1%7D%5En%20f%28x_i%29)
Assuming independence between the random sample, and replacing the density function we have this:
![L(\theta) = (\frac{1}{\sqrt{2\pi \sigma^2}})^n exp (-\frac{1}{2\sigma^2} \sum_{i=1}^n (X_i-\theta)^2)](https://tex.z-dn.net/?f=%20L%28%5Ctheta%29%20%3D%20%28%5Cfrac%7B1%7D%7B%5Csqrt%7B2%5Cpi%20%5Csigma%5E2%7D%7D%29%5En%20exp%20%28-%5Cfrac%7B1%7D%7B2%5Csigma%5E2%7D%20%5Csum_%7Bi%3D1%7D%5En%20%28X_i-%5Ctheta%29%5E2%29)
Taking the natural log on btoh sides we got:
![l(\theta) = -\frac{n}{2} ln(\sqrt{2\pi\sigma^2}) - \frac{1}{2\sigma^2} \sum_{i=1}^n (X_i -\theta)^2](https://tex.z-dn.net/?f=%20l%28%5Ctheta%29%20%3D%20-%5Cfrac%7Bn%7D%7B2%7D%20ln%28%5Csqrt%7B2%5Cpi%5Csigma%5E2%7D%29%20-%20%5Cfrac%7B1%7D%7B2%5Csigma%5E2%7D%20%5Csum_%7Bi%3D1%7D%5En%20%28X_i%20-%5Ctheta%29%5E2)
Now if we take the derivate respect
we will see this:
![l'(\theta) = \frac{1}{\sigma^2} \sum_{i=1}^n (X_i -\theta)](https://tex.z-dn.net/?f=%20l%27%28%5Ctheta%29%20%3D%20%5Cfrac%7B1%7D%7B%5Csigma%5E2%7D%20%5Csum_%7Bi%3D1%7D%5En%20%28X_i%20-%5Ctheta%29)
And then the maximum occurs when
, and that is only satisfied if and only if:
![\hat \theta = \bar X](https://tex.z-dn.net/?f=%20%5Chat%20%5Ctheta%20%3D%20%5Cbar%20X)