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Binomial Distribution
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It is time to figure out what Binomial distribution is.
To work with this distribution, we should import the binom object from scipy.stats, and then you can apply numerous functions to this distribution like pmf, sf, and cdf that were already learned.
Key characteristics:
This distribution is the same as the Bernoulli distribution, which is repeated several times.
Example:
Tossing a coin is a Bernoulli distribution, but tossing one coin 3 times creates a binomial distribution.
By the way, Y-axis defines the probability in percents, for the better understanding(in this chapter and the next).
Do you remember the function .cdf()? The function shows the probability of having k or fewer successes among n trials with the defined probability p. It is time to recall it!
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Imagine you passing a test that includes 12 questions; there are just two answers for each question (one of them is correct, another isn't correct). The probability of getting the right answer is 50% or 0.5. Here is the distribution:
You have excellent marks, and you know that if you receive less than 6 or exactly 7 points, you will spoil it.
- Import
binomobject. - Calculate the probability of receiving
6or less points in the test where the probability of answering right is0.5and the number of questions is12. - Calculate the probability of receiving exactly
7points in the test where the probability of answering right is0.5and the number of questions is12. - Calculate the whole probability.
解答
実践的な練習のためにデスクトップに切り替える下記のオプションのいずれかを利用して、現在の場所から続行するフィードバックありがとうございます！
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