6.3 Flashcard Binomial and Geometric Distributions

6.3 Flashcard Binomial and Geometric Distributions

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Flashcard

Mathematics

12th Grade

Hard

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15 questions

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1.

FLASHCARD QUESTION

Front

What is a binomial distribution?

Back

A binomial distribution is a probability distribution that summarizes the likelihood that a value will take one of two independent states and is defined by two parameters: the number of trials (n) and the probability of success (p).

2.

FLASHCARD QUESTION

Front

What is a geometric distribution?

Back

A geometric distribution models the number of trials needed to get the first success in a series of independent Bernoulli trials, where each trial has the same probability of success.

3.

FLASHCARD QUESTION

Front

What is the formula for calculating the mean of a binomial distribution?

Back

The mean (μ) of a binomial distribution is calculated using the formula: μ = n * p, where n is the number of trials and p is the probability of success.

4.

FLASHCARD QUESTION

Front

What is the formula for calculating the standard deviation of a binomial distribution?

Back

The standard deviation (σ) of a binomial distribution is calculated using the formula: σ = √(n * p * (1 - p)).

5.

FLASHCARD QUESTION

Front

How do you interpret the standard deviation in the context of a binomial distribution?

Back

The standard deviation indicates the average distance of the observed values from the mean, providing insight into the variability of the distribution.

6.

FLASHCARD QUESTION

Front

What is the probability of getting at least one success in a geometric distribution?

Back

The probability of getting at least one success in a geometric distribution is calculated as: P(X ≥ 1) = 1 - (1 - p)^k, where p is the probability of success and k is the number of trials.

7.

FLASHCARD QUESTION

Front

What does it mean if a random variable follows a binomial distribution?

Back

It means that the random variable represents the number of successes in a fixed number of independent trials, each with the same probability of success.

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