The Binomial Distribution is a cornerstone concept in the field of probability and statistics, particularly pivotal for students. This distribution helps in understanding phenomena where the outcome of an experiment or event can be classified into two distinct categories: success and failure.
Binomial Distribution: An Overview
At the heart of the binomial distribution, denoted as B(n, p), are certain conditions:
- The number of trials, n, is predetermined and finite.
- Each trial is independent, meaning the outcome of one trial does not influence another.
- The probability of success, p, is consistent across trials.
- Only two outcomes are possible: success or failure.
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The Binomial Formula
The probability of exactly x successes in n trials in a binomial distribution is given by:
Here, represents the binomial coefficient and is computed as .
Example Problems
Example 1: Quality Control in Manufacturing
Suppose a factory's production line has a 5% defect rate. If we randomly select 10 items for quality control, what is the probability that exactly 2 of them are defective?
Solution:
- Number of trials : 10
- Probability of a defective item : 0.05
- Desired number of defective items : 2
Using the binomial formula:
The binomial coefficient (\binom{10}{2}) is calculated as:
Thus,
So, there's about a 7.46% chance of finding exactly 2 defective items.
Example 2: Sports Probability
Consider a football player with a 70% chance of scoring a goal on each penalty kick. If they take 5 penalty kicks, what is the probability of scoring exactly 3 goals?
Solution:
- Number of penalty kicks : 5
- Probability of scoring : 0.70
- Desired number of goals : 3
Applying the binomial formula:
The binomial coefficient is:
Thus,
Hence, the player has approximately a 30.87% chance of scoring exactly 3 goals out of 5 kicks.