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Lesson 5.2 The Uniform Probability Distribution

Characteristics of the Uniform

For the uniform distribution, all values of the random variable are equally likely. For example, suppose the amount of time a college student waits in line at the college cafeteria during lunch time is uniformly distributed between 0 and 10 minutes. Since time follows a uniform distribution, the time from 0 to 10 minutes is equally likely.

The random variable X = the amount of time a college student spends in line at the college cafeteria during lunch time. All the times cannot be listed.

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Notation and Formulae

The function is f(X) = 1/(b - a) where a < X < b. The graph (shown below) is a horizontal line segment between the vertical lines X = a and X = b.

Basic uniform graph showing a rectangle
                        with base equal to b - a and height equal to
                        1/(b - a).

Notation:X ~ U(a, b)

Probability = the area of a rectangle = (base)(height)

Mean:

Uniform mean formula

Variance:

Uniform variance formula

Standard Deviation:

Uniform standard deviation formula
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Example

The amount of time a college student waits in line at the college cafeteria during lunch time is uniformly distributed between 0 and 10 minutes.

Let X = the amount of time a college student waits in line at the college cafeteria.

X ~ U(0, 10)

a = 0 and b = 10

f(X) = 1/(10 - 0) = 1/10 

Uniform graph where a = 0 and b = 10


Below are some typical problems:

Find the long term average.

m = (a + b)/2 = (0 + 10)/2 = 5 minutes


Find the Standard Deviation.

s = the square root of [(b - a)2/12] = the square root of

(10 - 0)2/12 = 2.9 minutes


Find the probability that a college student must wait less than 3 minutes.

Uniform graph showing area to
                                    the left of 3

P(X < 3) = (base)(height) = (3 - 0)(1/10) = 3/10.


Find the probability that a college student must wait between 3 and 7 minutes.

Uniform graph showing area
                                    between x = 3 and x = 7

P(3 < X < 7) = (base)(height) = (7 - 3)(1/10) = 4/10.


Find the probability that a college student must wait more than 8 minutes.

Uniform graph showing area to
                                    the right of x = 8

P(X > 8) = (base)(height) = (10 - 8)(1/10) = 2/10.


Find the probability that a college student must wait exactly 8 minutes.

Uniform graph showing 0 area
                                    for x = 8

P(X = 8) = (base)(height) = (0)(1/10) = 0.


Find the probability that a college student must wait more than 8 minutes when the college student has already waited more than 5 minutes.

Notice that the graph starts at X = 5 because we know that the college student has already waited more than 5 minutes.

This is a conditional probability (studied in Lesson 3). The base of the rectangle is no longer 10 - 0 = 10 but 10 - 5 = 5. Since the maximum area must be 1, the new height is 1/5.

P(X > 8|X > 5) = (base)(height) = (10 - 8)(1/5) = 2/5.

 Uniform conditional graph showing
                                  area to the right of x = 8

Another way to do the problem is to use the conditional probability equation with the original function f(X) = 1/10 where 0 < X < 10:

P(A|B) = P(A AND B) / P(B).

In this case A is X > 8 and B is X > 5.

So, P(X > 8|X > 5) = P(X > 8 AND X > 5) / P(X > 5) = P(X > 8) / P(X > 5) = [2/10] / [5/10] = 2/5. 

Uniform graph showing
                                            how to do conditional
                                            differently


Find the 90th percentile (find the waiting time that has 90% of all other waiting times falling below it).

 Uniform graph showing the
                                      90th percentile amd k

Let k = the 90th percentile. The area to the left of k is 0.90 (remember, the largest area is 1). AREA = (base)(height). So, 0.90 = (k - 0)(1/10)

(0.90)(10) = (k)(1/10)(10)

9 minutes = k

90% of the waiting times fall below 9 minutes. Another way to say this is that 90% of the time, a college student must wait less than 9 minutes.

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Uniform Problem Using TI-83 or TI-84 calculators

Example

The following problem is an example of a uniform probability problem solved by using TI-83 or TI-84 calculators. Close the window when you are finished viewing the example.

 

Think About It

Do Try-It examples in Introductory Statistics.

Please continue to the next section of this lesson.

 

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Up » 5.1 Continuous Probability » 5.2 Uniform Probability » 5.3 Exponentrial Probability

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