How Can I Calculate Probabilities for Event Success Rates?

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To calculate the probability of event success rates, a binomial model is recommended, which uses the formula for the probability of exactly k successes in n trials: \binom{n}{k}p^k(1-p)^{n-k}. To find the probability of achieving at least k successes, sum the probabilities for all values greater than or equal to k. The term \binom{n}{k} represents the binomial coefficient, indicating the number of ways to choose k successes from n attempts. Understanding factorial notation is also essential, as it is used in calculating these coefficients. This approach provides a structured way to analyze success rates in probabilistic scenarios.
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I have near to no knowledge of statistics, and I want to build a statistical model that can help me calculate %chance of an event happening in situations of type:

every try has 25% success rate
after 6 tries, what are the probabilities of having succeeded at least 5times? After 12tries?

or

each shot has 42% success rate
after 5 tries, how what are the probabilities of succeding at least 4times?


How can I calculate probabilities like these?
 
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Sounds like you want a binomial model. Given probability of success p and n attempts, the probability of exactly k successes is:

\binom{n}{k}p^k(1-p)^{n-k}

Of course, to figure out the probability of at least k successes, you have to add up these probabilities for every value greater than or equal to k.
 
what does the n above k in brackets mean?
 
\binom{n}{k} is the "binomial coefficient". It is the coefficient of xkyn-k in (x+y)n as well as the kth term in the nth line in Pascal's triangle and can be calculated as \frac{n!}{k!(n-k)!}.

It is sometimes written nCk and our British colleagues seem to refer to it as "n choose k" since it is also the number of different ways one can choose k items from a set of n items.
 
And just in case you do not know what x! means: it means x factorial:

x! = 1\times 2\times 3 \times \ldots \times (x-1) \times x
 
Ok, thanks for explanation!
 
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