Binomial distribution: Difference between revisions
From ACT Wiki
Jump to navigationJump to search
imported>Doug Williamson (Align with Glossary and link with Poisson distribution page.) |
imported>Doug Williamson (Add example from ACT ESA exam, April 2014, Q7.) |
||
| Line 11: | Line 11: | ||
#The trials are independent and | #The trials are independent and | ||
#Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials. | #Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials. | ||
For example, the total number of sales achieved in a fixed number of sales appointments, assuming the probability of achieving a sale remains constant for each appointment. | |||
Revision as of 14:08, 5 August 2014
Statistics.
A discrete probability distribution built up from a series of binomial trials.
The binomial distribution can be a useful model for processes where:
- The process consists of a whole number of identical trials or situations (n).
- Each trial results in just one of only two possible outcomes (eg success or failure).
- The probability of success (p) remains constant for each trial.
- The trials are independent and
- Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials.
For example, the total number of sales achieved in a fixed number of sales appointments, assuming the probability of achieving a sale remains constant for each appointment.
