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- Probability distribution function
This module introduces the Probability Distribution Function (PDF) and its characteristics.
A discrete
probability distribution function has two characteristics:
- Each probability is between 0 and 1, inclusive.
- The sum of the probabilities is 1.
A child psychologist is interested in the number of times a newborn baby's crying wakes its mother after midnight. For a random sample of 50 mothers, the following information was obtained. Let
= the number of times a newborn wakes its mother after midnight. For this example,
= 0, 1, 2, 3, 4, 5.
= probability that
takes on a value
.
|
|
0 |
|
1 |
|
2 |
|
3 |
|
4 |
|
5 |
|
takes on the values 0, 1, 2, 3, 4, 5.
This is a discrete
because
- Each
is between 0 and 1, inclusive.
- The sum of the probabilities is 1, that is,
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Suppose Nancy has classes
3 days a week. She attends classes 3 days a week
80% of the time,
2 days 15% of the time,
1 day 4% of the time, and
no days 1% of the time. Suppose one week is randomly selected.
Suppose one week is randomly chosen. Construct a probability distribution table (called a
table) like the one in the previous example. The table should have two columns labeled
and
. What does the
column sum to?
|
|
0 |
0.01 |
1 |
0.04 |
2 |
0.15 |
3 |
0.80 |
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Source:
OpenStax, Collaborative statistics. OpenStax CNX. Jul 03, 2012 Download for free at http://cnx.org/content/col10522/1.40
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