Review the key concepts, formulae, and examples before starting your quiz.
🔑Concepts
A Binomial distribution models the number of successes in a fixed number of independent trials. It is denoted as , where is the number of trials and is the probability of success.
The conditions for a Binomial distribution (often remembered as BINS) are: Binary outcomes (success or failure), Independent trials, fixed Number of trials (), and constant probability of Success ().
The discrete random variable can take any integer value such that .
The complement probability (failure) is often denoted as , where .
IB AI students are expected to use a Graphic Display Calculator (GDC) for most calculations using functions like 'Binomial PDF' (for ) and 'Binomial CDF' (for ).
📐Formulae
💡Examples
Problem 1:
A fair six-sided die is rolled times. Let be the number of times a is rolled. Find the probability that a is rolled exactly times.
Solution:
Explanation:
Identify the parameters: , , and . Use the Binomial Probability Density Function (binompdf) on the GDC with these values.
Problem 2:
In a large shipment of light bulbs, are known to be defective. A random sample of bulbs is tested. Find the probability that at most bulbs are defective.
Solution:
Explanation:
This is a cumulative probability problem where and . Use the Binomial Cumulative Distribution Function (binomcdf) on the GDC with lower bound and upper bound .
Problem 3:
A student takes a multiple-choice test with questions. Each question has options, and only one is correct. If the student guesses every answer, calculate the expected number of correct answers and the standard deviation.
Solution:
Explanation:
The number of trials is and the probability of success is . The mean (expectation) is and the standard deviation is .