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Answer:
<em>The ladder touches the wall at 24 feet from the ground.</em>
Step-by-step explanation:
The wall of the building, the ground, and the ladder form a right triangle, whose longer side is the length of the ladder.
In any right triangle, we can apply Pythagora's theorem to find any missing side length.
The ladder is 26 feet in length, the distance from the bottom of the ladder and the building is 10 feet. Calling H to the distance above the ground where the ladder touches the wall, then:
Calculating:
Solving:
H=24 feet
The ladder touches the wall at 24 feet from the ground.
There are two triangles in the figure(triangular prism) option third is correct.
<h3>What is a triangular prism?</h3>When a triangle is, stretch it out to produce a stack of triangles, one on top of the other. A triangular prism is a name given to this novel 3D object.
The complete question is:
How many triangles are needed to draw the net of this object?
- 4
- 3
- 2
- 1
For the figure please refer to the attached picture.
As we can see in the figure we have given a triangular prism:
The triangular prism has two triangles.
A triangle for the base of the prism and a triangle for the top of the prism.
The lateral faces of the prism are rectangular.
Thus, there are two triangles in the figure(triangular prism) option third is correct.
Learn more about triangular prisms here:
#SPJ1
Answer:
a. .
b.
Step-by-step explanation:
By the definition, the expected value of a random variable X with probability mass function p is given by where the sum runs over all the posible values of X. Given a function g, the random variable Y=g(X) is defined. Note that the function g induces a probability mass function P' given by P'(Y=k) = P(X=g^{-1}(k)) when the function g is bijective.
a. Note that for 1/3ln(2)+1/6ln(5) by choosing the function g(x) = ln(x) the expression coincides with E(g(x)), because if Y = g(x) then E(Y) = P'(Y=1)*ln(1)+P'(Y=2)*ln(2)+P'(Y=5)*ln(5) = P(X=1)*ln(1)+P(X=2)*ln(2)+P(X=5)*ln(5).
b. On the same fashion, the function g(x) = xe^{xt} fullfills the expression of E[g(X)]