Another quadrilateral that you might see is called a rhombus. All four sides of a rhombus are congruent. Its properties include that each pair of opposite sides is parallel, also making it a parallelogram. In summary, all squares are rectangles, but not all rectangles are squares.
Answer:
We have been given a unit circle which is cut at k different points to produce k different arcs. Now we can see firstly that the sum of lengths of all k arks is equal to the circumference:

Now consider the largest arc to have length \small l . And we represent all the other arcs to be some constant times this length.
we get :

where C(i) is a constant coefficient obviously between 0 and 1.

All that I want to say by using this step is that after we choose the largest length (or any length for that matter) the other fractions appear according to the above summation constraint. [This step may even be avoided depending on how much precaution you wanna take when deriving a relation.]
So since there is no bias, and \small l may come out to be any value from [0 , 2π] with equal probability, the expected value is then defined as just the average value of all the samples.
We already know the sum so it is easy to compute the average :

Isolate the variable by dividing each side by factors that don't contain the variable.
f=e-g/d
Answer:
1
Step-by-step explanation:
Start at -0.5 and go toward 0.5.
From -0.5 to zero, it's a distance of 0.5.
From zero to 0.5, it's also a distance of 0.5.
Add the two distances, 0.5 + 0.5 = 1.
The distance between -0.5 to 0.5 is 1.