Simplified C.D.F. Formula: Get the Answer Now!

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In summary, the simplified formula for the c.d.f., F(n) = (P \leq n), is (1-\alpha)^{n+1}. This can be derived by using the formula \sum_{k=0}^{n}r^k=\frac{1-r^{n+1}}{1-r} and simplifying the expression \alpha \sum_{k=0}^{n}r^k=\frac{1-(1-\alpha)^{n+1}}{1-(1-\alpha)} to get \frac{-(1-\alpha)^{n+1}}{-1} which simplifies to (1-\alpha)^{n+1}.
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needhelp83
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Derive a simplified formula for the c.d.f., F(n) = (P [tex]\leq [/tex] n), using:

[tex]\sum_{k=0}^{n}r^k=\frac{1-r^{n+1}}{1-r} [/tex]


[tex]p(n)=\alpha (1-\alpha)^n [/tex]

[tex]\alpha \sum_{k=0}^{n}r^k=\frac{1-(1-\alpha)^{n+1}}{1-(1-\alpha)} [/tex]

How do I break this down to a simplified version?
 
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  • #2
Alright, I may have figured this out hopefully...

[tex]
\alpha \sum_{k=0}^{n}r^k=\frac{1-(1-\alpha)^{n+1}}{1-(1-\alpha)}
[/tex]

[tex]
\alpha \frac{1-(1-\alpha)^{n+1}}{1-(1-\alpha)}
[/tex]


[tex]
\alpha \frac{-(1-\alpha)^{n+1}}{-1+\alpha}
[/tex]

Is this right?


[tex]
\frac{-(1-\alpha)^{n+1}}{-1}
[/tex]


[tex]
(1-\alpha)^{n+1}
[/tex]
 

1. What is the Simplified C.D.F. Formula?

The Simplified C.D.F. Formula is a mathematical formula used to calculate the cumulative distribution function of a continuous random variable. It is often used in probability and statistics to determine the probability that a random variable will fall below a certain value.

2. How is the Simplified C.D.F. Formula different from other C.D.F. formulas?

The Simplified C.D.F. Formula is a simplified version of other C.D.F. formulas, such as the normal distribution C.D.F. formula or the exponential distribution C.D.F. formula. It is a more general formula that can be applied to any continuous random variable, whereas other C.D.F. formulas are specific to certain distributions.

3. What are the inputs of the Simplified C.D.F. Formula?

The inputs of the Simplified C.D.F. Formula are the value of the random variable, the mean, and the standard deviation. These values are used to calculate the probability that the random variable falls below a certain value.

4. How can the Simplified C.D.F. Formula be used in real-world applications?

The Simplified C.D.F. Formula can be used in a variety of real-world applications, such as in finance to calculate the probability of a stock price falling below a certain level, in engineering to determine the probability of a bridge collapsing under a certain weight, or in medicine to predict the likelihood of a patient experiencing a certain side effect from a medication.

5. Are there any limitations to the Simplified C.D.F. Formula?

Like any mathematical formula, the Simplified C.D.F. Formula has its limitations. It assumes that the random variable follows a continuous distribution, and may not be accurate for discrete distributions. It also assumes that the mean and standard deviation are known, which may not always be the case in real-world applications.

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