Answer:
72 square units
Step-by-step explanation:
The figure shown has a uniform horizontal cross section, so is equivalent to a rectangle with length 12 and height 6. Its area is given by the rectangle formula:
A = LW
A = (12)(6) = 72 . . . . square units
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<em>Additional comment</em>
Essentially, the semicircle removed from the left side is tacked onto the right side. The rectangle area is unchanged by that.
Answer:
<em>Numbers: 6 and -2</em>
Step-by-step explanation:
<u>Equations</u>
This question can be solved by inspection. It's just a matter of factoring 12 into two factors that sum 4. Both numbers must be of different signs and they are 6 and -2. Their sum is indeed 6-2=4 and their product is 6*(-2)=-12.
However, we'll solve it by the use of equations. Let's call x and y to the numbers. They must comply:
![x+y=4\qquad\qquad [1]](https://tex.z-dn.net/?f=x%2By%3D4%5Cqquad%5Cqquad%20%5B1%5D)
![x.y=-12\qquad\qquad [2]](https://tex.z-dn.net/?f=x.y%3D-12%5Cqquad%5Cqquad%20%5B2%5D)
Solving [1] for y:

Substituting in [2]

Operating:

Rearranging:

Solving with the quadratic formula:

With a=1, b=-4, c=-12:



The solutions are:


This confirms the preliminary results.
Numbers: 6 and -2
Answer:
So the height is 12
Step-by-step explanation:
Let W be the width
Let W- 4 be the height
W2 +(W-4)2 = 400
So: W2 -4W-192 =0
One uses the quadratic solution:
W = (4 + (16 + 4*192).5)/2 = 16
Answer:
Eat them. )llllllllllllllllllllllllll)
Answer:
(b) (c) (a)
Step-by-step explanation:
Standard Normal distribution has a higher peak in the center, with more area in this región, hence it has less area in its tails.
Student's t-Distribution has a shape similar to the Standard Normal Distribution, with the difference that the shape depends on the degree of freedom. When the degree of freedom is smaller the distribution becomes flatter, so it has more area in its tails.
Student's t-Distributionwith 1515 degrees of freedom has mores area in the tails than the Student's t-Distribution with 2020 degrees of freedom and the latter has more area than Standard Normal Distribution