Deriving the binomial distribution formula

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SUMMARY

The discussion centers on the derivation of the binomial distribution formula, specifically b(x;n,p) = nCx * px * qn-x, where nCx represents the number of combinations of n trials taken x at a time. The term "specified order" refers to the arrangement of successes and failures in a sequence, which is crucial for calculating probabilities in binomial experiments. By multiplying the probabilities of successes (p) and failures (q) for a specific order, and then incorporating nCx, one can derive the overall probability of x successes in n trials. An example using a dice roll illustrates how to apply this formula in practical scenarios.

PREREQUISITES
  • Understanding of binomial experiments
  • Familiarity with probability concepts
  • Knowledge of combinations, specifically nCx
  • Basic skills in algebra for manipulating formulas
NEXT STEPS
  • Study the derivation of the binomial distribution in detail
  • Learn about the properties of binomial coefficients (nCx)
  • Explore applications of the binomial distribution in real-world scenarios
  • Investigate related distributions, such as the normal approximation to the binomial distribution
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Students of statistics, mathematicians, data analysts, and anyone interested in understanding probability distributions and their applications in various fields.

Saladsamurai
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I am trying to follow along with this derivation of the binomial distribution formula:
b(x;n,p) = nCx*pxqn-x

But I do not really understand the meaning of the part on bold. What is this "specified order" business now? I feel like I am missing something big here.

Let us now generalize the above illustration to yield a formula for b(x;n,p). That is, we wish to find a formula that gives the probability of x successes in n trials for a binomial experiment. First, consider the probability of x successes and n — x failures in a specified order. Since the trials are independent, we can multiply all the probabilities corresponding to the different outcomes. Each success occurs with probability p and each failure with probability q = 1 — p. Therefore, the probability for the specified order is pxqn-x. number of sample points in the experiment that have x successes and n — x failures. This number is equal to the number of partitions of n outcomes into two groups with x in one group and n—x in the other and is written nCx as introduced in Section 2.3. Because these partitions are mutually exclusive, we add the probabilities of all the different partitions to obtain the general formula, or simply multiply pxqn-x by nCx.
 
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Think about what the "nCx" part of the formula does.

Let's say we're rolling a regular dice 4 times, and we want the probability of a 6 only once. We know this would consist of 1 success and 3 failures ( \frac{1}{6}\frac{}{} )( \frac{5}{6} )3, however it does not account for which roll we get the 6, since it can occur in any 1 out of the 4 rolls, we multiply by 4C1.

So that "specific order" business is to eliminate the need to account for exactly when our successes occur

Does that make sense?
 

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