Learning objectives
We begin by defining 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) = for 0 ≤ x ≤ 20. x = a real number. The graph of f(x) = is a horizontal line. However, since 0 ≤ x ≤ 20, f(x) is restricted to the portion between x = 0 and x = 20, inclusive.
View original figure (external; image not reproduced in this text edition)
Original figure description: 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) = for 0 ≤ x ≤ 20.
The graph of f(x) = is a horizontal line segment when 0 ≤ x ≤ 20.
The area between f(x) = where 0 ≤ x ≤ 20 and the x-axis is the area of a rectangle with base = 20 and height = .
Suppose we want to find the area between f(x) = and the x-axis where 0 < x < 2.
View original figure (external; image not reproduced in this text edition)
Original figure description: 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.
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) = and the x-axis where 4 < x < 15.
View original figure (external; image not reproduced in this text edition)
Original figure description: 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.
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) = 0
View original figure (external; image not reproduced in this text edition)
Original figure description: 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), which can also 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 also 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).
View original figure (external; image not reproduced in this text edition)
Original figure description: 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) = , 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.
View original figure (external; image not reproduced in this text edition)
Original figure description: 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
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).
View original figure (external; image not reproduced in this text edition)
Original figure description: 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?
View original figure (external; image not reproduced in this text edition)
Original figure description: 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?
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Original figure description: 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?
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Original figure description: 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 < ___)
View original figure (external; image not reproduced in this text edition)
Original figure description: 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 < ___)
View original figure (external; image not reproduced in this text edition)
Original figure description: 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 , and the function is restricted to 0 ≤ x ≤ 5. What is P(x < 0)?
f(x), a continuous probability function, is equal to , 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.
View original figure (external; image not reproduced in this text edition)
Original figure description: A graph is shown. An unlabeled x axis is measured in increments of 1 from 0 to 10. The y-axis has one measurement of 1/9. A box is drawn on the graph, stretching from 0 to 9 on the x axis, and up to the 1/9 measurement on the y axis. The box is shaded blue between the measurements of 6 and 8.
Find the probability that x falls in the shaded area.
View original figure (external; image not reproduced in this text edition)
Original figure description: A graph is shown. An unlabeled x axis is measured in increments of 1 from 0 to 10. The y-axis has one measurement of 1/8. A box is drawn on the graph, stretching from 0 to 8.5 on the x axis, and up to the 1/8 measurement on the y axis. The box is shaded between the measurements of 0and 5.
0.625
Find the probability that x falls in the shaded area.
View original figure (external; image not reproduced in this text edition)
Original figure description: A graph is shown. An unlabeled x axis is measured in increments of 1 from 0 to 10. The y-axis has one measurement of 1/10. A box is drawn on the graph, stretching from 0 to 10 on the x axis, and up to the 1/10 measurement on the y axis. The box is shaded blue between the measurements 2.5 and 5.5.
f(x), a continuous probability function, is equal to and the function is restricted to 1 ≤ x ≤ 4. Describe
The probability is equal to the area from x = to x = 4 above the x-axis and up to f(x) = .
Homework
For each probability and percentile problem, draw the picture.
Consider the following experiment. You are one of 100 people enlisted to take part in a study to determine percentage of nurses in America with an R.N. (registered nurse) degree. You ask nurses if they have an R.N. degree. The nurses answer yes or no. You then calculate the percentage of nurses with an R.N. degree. You give that percentage to your supervisor.
- What part of the experiment will yield discrete data?
- What part of the experiment will yield continuous data?
When age is rounded to the nearest year, do the data stay continuous, or do they become discrete? Why?
Age is a measurement, regardless of the accuracy used.