https://file.aiquickdraw.com/mathbot/file/17244205793188r39uni4.jpg

Use this P(x)= n C_{x} * p ^ x * (1 - p) ^ (n - x) for the probability.

The image you uploaded contains information about probability and seems to reference a binomial probability formula, \( P(x) = \binom{n}{x} p^x (1 - p)^{n - x} \), where:

- \( n \) is the number of trials,
- \( x \) is the number of successes,
- \( p \) is the probability of success on a single trial,
- \( \binom{n}{x} \) is the binomial coefficient, which calculates the number of ways to choose \( x \) successes out of \( n \) trials.

To assist you better, could you specify the values for \( n \), \( x \), and \( p \), or provide more context from the problem so I can help you calculate the probability or interpret the information?

If you're calculating a specific probability, please share the necessary details.

Would you like me to extract more details or clarify anything specific?  
Here are 5 relative questions to guide further exploration:

1. What values are given for \( n \), \( x \), and \( p \) in your problem?
2. Are you interested in calculating a single probability or cumulative probabilities?
3. Does the table in the image provide any specific values that relate to \( n \), \( x \), or \( p \)?
4. Is there any specific application or scenario described in the text related to this probability distribution?
5. Would you like to see a step-by-step explanation of how to use the binomial probability formula?

**Tip:** When working with binomial distributions, always ensure that the trials are independent, and the probability of success remains constant across trials.

Explore the binomial probability formula P(x) = n C_x * p^x * (1 - p)^(n - x) and its application in calculating probabilities of successes in a series of independent trials. This page provides an explanation, examples, and step-by-step calculations.

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