Binomial distribution: Difference between revisions
From ACT Wiki
Jump to navigationJump to search
imported>Doug Williamson (Add 'limited' before 'whole number' to differentiate from Poisson distribution.) |
imported>Doug Williamson (Amend from 'useful' model to 'appropriate'.) |
||
Line 4: | Line 4: | ||
The binomial distribution can be | The binomial distribution can be an appropriate model for processes where: | ||
#The process consists of a limited whole number of identical trials or situations (n). | #The process consists of a limited whole number of identical trials or situations (n). |
Revision as of 11:19, 7 August 2014
Statistics.
A discrete probability distribution built up from a series of binomial trials.
The binomial distribution can be an appropriate model for processes where:
- The process consists of a limited 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.