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5.1 Properties of continuous probability density functions  (Page 2/6)

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In this chapter and the next, we will study the uniform distribution, the exponential distribution, and the normal distribution. The following graphs illustrate these distributions.

This graph shows a uniform distribution. The horizontal axis ranges from 0 to 10. The distribution is modeled by a rectangle extending from x = 2 to x = 8.8. A region from x = 3 to x = 6 is shaded inside the rectangle. The shaded area represents P(3 x < 6).
The graph shows a Uniform Distribution with the area between x = 3 and x = 6 shaded to represent the probability that the value of the random variable X is in the interval between three and six.
The graph shows an Exponential Distribution with the area between x = 2 and x = 4 shaded to represent the probability that the value of the random variable X is in the interval between two and four.
This graph shows an exponential distribution. The graph slopes downward. It begins at a point on the y-axis and approaches the x-axis at the right edge of the graph. The region under the graph from x = 2 to x = 4 is shaded to represent P(2 < x < 4).
The graph shows the Standard Normal Distribution with the area between x = 1 and x = 2 shaded to represent the probability that the value of the random variable X is in the interval between one and two.

We begin by defining formally a continuous probability density function. We use the function notation f ( x ). Intermediate algebra may have been your first formal introduction to functions. In the study of probability, the functions we study are special. We define the function f ( x ) so that the area between it and the x-axis is equal to a probability. Since the maximum probability is one, the maximum area is also one. For continuous probability distributions, PROBABILITY = AREA.

Consider the function f ( x ) = 1 20 for 0 ≤ x ≤ 20. x = a real number. The graph of f ( x ) = 1 20 is a horizontal line. However, since 0 ≤ x ≤ 20, f ( x ) is restricted to the portion between x = 0 and x = 20, inclusive.

This shows the graph of the function f(x) = 1/20. A horiztonal line ranges from the point (0, 1/20) to the point (20, 1/20). A vertical line extends from the x-axis to the end of the line at point (20, 1/20) creating a rectangle.

f ( x ) = 1 20 for 0 ≤ x ≤ 20.

The graph of f ( x ) = 1 20 is a horizontal line segment when 0 ≤ x ≤ 20.

The area between f ( x ) = 1 20 where 0 ≤ x ≤ 20 and the x -axis is the area of a rectangle with base = 20 and height = 1 20 .

AREA = 20 ( 1 20 ) = 1

Suppose we want to find the area between f( x ) = 1 20 and the x -axis where 0< x <2.

This shows the graph of the function f(x) = 1/20. A horiztonal line ranges from the point (0, 1/20) to the point (20, 1/20). A vertical line extends from the x-axis to the end of the line at point (20, 1/20) creating a rectangle. A region is shaded inside the rectangle from x = 0 to x = 2.

AREA  =   ( 2   –   0 ) ( 1 20 )   =   0.1

( 2 – 0 ) = 2 = base of a rectangle

Reminder

area of a rectangle = (base)(height).

The area corresponds to a probability. The probability that x is between zero and two is 0.1, which can be written mathematically as P (0< x <2) = P ( x <2) = 0.1.

Suppose we want to find the area between f ( x ) = 1 20 and the x -axis where 4< x <15.

This shows the graph of the function f(x) = 1/20. A horiztonal line ranges from the point (0, 1/20) to the point (20, 1/20). A vertical line extends from the x-axis to the end of the line at point (20, 1/20) creating a rectangle. A region is shaded inside the rectangle from x = 4 to x = 15.

AREA  =   ( 15   –   4 ) ( 1 20 )   =   0.55

AREA  =   ( 15   –   4 ) ( 1 20 )   =   0.55

( 15   –   4 )   =   11   =  the base of a rectangle

The area corresponds to the probability P (4< x <15) = 0.55.

Suppose we want to find P ( x = 15). On an x-y graph, x = 15 is a vertical line. A vertical line has no width (or zero width). Therefore, P ( x = 15) = (base)(height) = (0) ( 1 20 ) = 0

This shows the graph of the function f(x) = 1/20. A horiztonal line ranges from the point (0, 1/20) to the point (20, 1/20). A vertical line extends from the x-axis to the end of the line at point (20, 1/20) creating a rectangle. A vertical line extends from the horizontal axis to the graph at x = 15.

P ( X ≤ x ) (can be written as P ( X < x ) for continuous distributions) is called the cumulative distribution function or CDF. Notice the "less than or equal to" symbol. We can use the CDF to calculate P ( X > x ). The CDF gives "area to the left" and P ( X > x ) gives "area to the right." We calculate P ( X > x ) for continuous distributions as follows: P ( X > x ) = 1 – P ( X < x ).

This shows the graph of the function f(x) = 1/20. A horiztonal line ranges from the point (0, 1/20) to the point (20, 1/20). A vertical line extends from the x-axis to the end of the line at point (20, 1/20) creating a rectangle. The area to the left of a value, x, is shaded.

Label the graph with f ( x ) and x . Scale the x and y axes with the maximum x and y values. f ( x ) = 1 20 , 0 ≤ x ≤ 20.

To calculate the probability that x is between two values, look at the following graph. Shade the region between x = 2.3 and x = 12.7. Then calculate the shaded area of a rectangle.

This shows the graph of the function f(x) = 1/20. A horiztonal line ranges from the point (0, 1/20) to the point (20, 1/20). A vertical line extends from the x-axis to the end of the line at point (20, 1/20) creating a rectangle. A region is shaded inside the rectangle from x = 2.3 to x = 12.7

P ( 2.3 < x < 12.7 ) = ( base ) ( height ) = ( 12.7 − 2.3 ) ( 1 20 ) = 0.52

Try it

Consider the function f ( x ) = 1 8 for 0 ≤ x ≤ 8. Draw the graph of f ( x ) and find P (2.5< x <7.5).

P (2.5< x <7.5) = 0.625

Chapter review

The probability density function (pdf) is used to describe probabilities for continuous random variables. The area under the density curve between two points corresponds to the probability that the variable falls between those two values. In other words, the area under the density curve between points a and b is equal to P ( a < x < b ). The cumulative distribution function (cdf) gives the probability as an area. If X is a continuous random variable, the probability density function (pdf), f ( x ), is used to draw the graph of the probability distribution. The total area under the graph of f ( x ) is one. The area under the graph of f ( x ) and between values a and b gives the probability P ( a < x < b ).

The graph on the left shows a general density curve, y = f(x). The region under the curve and above the x-axis is shaded. The area of the shaded region is equal to 1. This shows that all possible outcomes are represented by the curve. The graph on the right shows the same density curve. Vertical lines x = a and x = b extend from the axis to the curve, and the area between the lines is shaded. The area of the shaded region represents the probabilit ythat a value x falls between a and b.

The cumulative distribution function (cdf) of X is defined by P ( X ≤ x ). It is a function of x that gives the probability that the random variable is less than or equal to x .

Formula review

Probability density function (pdf) f ( x ):

  • f ( x ) ≥ 0
  • The total area under the curve f ( x ) is one.

Cumulative distribution function (cdf): P ( X ≤ x )

Which type of distribution does the graph illustrate?

The horizontal axis ranges from 0 to 10. The distribution is modeled by a rectangle extending from x = 3 to x =8.

Uniform Distribution

Which type of distribution does the graph illustrate?

This graph slopes downward. It begins at a point on the y-axis and approaches the x-axis at the right edge of the graph.

Which type of distribution does the graph illustrate?

This graph shows a bell-shaped graph. The symmetric graph reaches maximum height at x = 0 and slopes downward gradually to the x-axis on each side of the peak.

Normal Distribution

What does the shaded area represent? P (___< x <___)

This graph shows a uniform distribution. The horizontal axis ranges from 0 to 10. The distribution is modeled by a rectangle extending from x = 1 to x = 8. A region from x = 2 to x = 5 is shaded inside the rectangle.

What does the shaded area represent? P (___< x <___)

This graph shows an exponential distribution. The graph slopes downward. It begins at a point on the y-axis and approaches the x-axis at the right edge of the graph. The region under the graph from x = 6 to x = 7 is shaded.

P (6< x <7)

For a continuous probablity distribution, 0 ≤ x ≤ 15. What is P ( x >15)?

What is the area under f ( x ) if the function is a continuous probability density function?

one

For a continuous probability distribution, 0 ≤ x ≤ 10. What is P ( x = 7)?

A continuous probability function is restricted to the portion between x = 0 and 7. What is P ( x = 10)?

zero

f ( x ) for a continuous probability function is 1 5 , and the function is restricted to 0 ≤ x ≤ 5. What is P ( x <0)?

f ( x ), a continuous probability function, is equal to 1 12 , and the function is restricted to 0 ≤ x ≤ 12. What is P (0< x <12)?

one

Find the probability that x falls in the shaded area.

Find the probability that x falls in the shaded area.

0.625

Find the probability that x falls in the shaded area.

f ( x ), a continuous probability function, is equal to 1 3 and the function is restricted to 1 ≤ x ≤ 4. Describe P ( x > 3 2 ) .

The probability is equal to the area from x = 3 2 to x = 4 above the x-axis and up to f ( x ) = 1 3 .
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Source:  OpenStax, Introductory statistics. OpenStax CNX. Aug 09, 2016 Download for free at http://legacy.cnx.org/content/col11776/1.26
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