Understanding the Generalized Binomial Formula: Exploring the Role of n+1/2

In summary, the conversation discusses the definition of the expression \left(\begin{array}{c} x \\ n \end{array}\right) when x is not an integer and when m and n are integers. The conversation also explores how to transform x^(n+1/2) to x^(n) in a summation.
  • #1
toni
19
0
I stuck at the second "="...i know it goes like this because the formula...i just someone explain to me why it works like that.

thank you soooo much!
 

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  • #2
What is the definition of
[tex]\left(\begin{array}{c} x \\ n \end{array}\right)[/tex]
when x is not an integer?

If you cannot answer that, can you say what
[tex]\left(\begin{array}{c} m \\ n \end{array}\right)[/tex]
means when m and n are integers? What do you get if you replace the "m" with "x"?
 
  • #3
this is what I've done...still far from the destination

Sum(0 to infinity) (-1)^n [(1)(3)...(2n-1) x^(n+1/2) / (2n)!]

donno how to transform x^(n+1/2) to x^(n)?...thank you for your help!
 
  • #4
where did the n+1/2 come from?
 

What is the Generalized Binomial Formula?

The Generalized Binomial Formula is a mathematical formula used to calculate the probability of a specific number of successes in a certain number of trials, where the outcome of each trial is either success or failure. It is an extension of the regular Binomial Formula, which only considers the probability of a single number of successes.

How is the Generalized Binomial Formula used?

The Generalized Binomial Formula is used to calculate the probability of a specific number of successes in a certain number of independent trials, where the probability of success remains constant for each trial. It is commonly used in statistics, probability, and other fields of mathematics to analyze and predict the outcome of repeated events.

What are the components of the Generalized Binomial Formula?

The components of the Generalized Binomial Formula are:
- n: the total number of trials
- x: the number of successes
- p: the probability of success in a single trial
- q: the probability of failure in a single trial (1-p)
- nCx: the number of combinations of x successes in n trials
- p^x: the probability of x successes
- q^(n-x): the probability of (n-x) failures

What is the difference between the Generalized Binomial Formula and the regular Binomial Formula?

The regular Binomial Formula only calculates the probability of a specific number of successes in a single trial, while the Generalized Binomial Formula takes into account multiple trials and calculates the probability of a specific number of successes in those trials. Additionally, the Generalized Binomial Formula allows for varying probabilities of success in each trial, while the regular Binomial Formula assumes a constant probability.

Can the Generalized Binomial Formula be applied to real-world scenarios?

Yes, the Generalized Binomial Formula can be applied to real-world scenarios such as predicting the probability of a certain number of people winning a lottery, the chances of flipping a coin a certain number of times and getting a specific number of heads, or the likelihood of a certain number of students passing a test. It can also be used in fields such as genetics, where it can be used to calculate the probability of a certain number of offspring inheriting a specific trait.

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