Is this a valid way to calculate statistically probable value?

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The discussion centers on calculating the statistically probable value of a normally distributed outcome, defined as zero for values less than a threshold (a) and as x-a for values above it. The proposed calculation involves integrating the product of the probability density function f(x) and the function g(x) from a to infinity. Clarification is provided that the term "statistically probable value" likely refers to "expected value," which is a standard concept in statistics. The integration approach aligns with established statistical principles, confirming its validity for calculating expected values under the defined conditions. Overall, the method presented is appropriate for determining the expected value in this context.
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Good day,

Assume an event with a normally distributed numerical outcome. Call the outcome x. Assume that any outcome less than a particular value (called a) has a value of zero and any outcome greater than a has a value of x-a. Call the probability curve of the normal distribution f(x) and x-a = g(x). I am calculating the statistically probable value of any event as

Integral from a to infinity of [f(x) times g(x)] dx

Is this valid?

I hope that I explained this sufficiently. Thank you for your help.
 
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30osk said:
Good day,

Assume an event with a normally distributed numerical outcome. Call the outcome x. Assume that any outcome less than a particular value (called a) has a value of zero and any outcome greater than a has a value of x-a. Call the probability curve of the normal distribution f(x) and x-a = g(x). I am calculating the statistically probable value of any event as

Integral from a to infinity of [f(x) times g(x)] dx

Is this valid?

I hope that I explained this sufficiently. Thank you for your help.

Could be clearer! I think that by "statistically probable value" you mean "expected value" (otherwise, I don't know what you mean by "statistically probable"). If so, yes, the "expected value" of any function g, of a random variable x with probability density function f, is given by
\int_{-\infty}^\infty f(x)g(x)dx
If g(x)= 0 for x< a then that is
\int_a^\infty f(x)g(x)dx
 
Thanks for your reply. Your presumption is correct, I think. Since I am ignorant of the teminology of statistics, the following is not an argument but an explanation of why I used those words. I didn't use "expected probability" because I don't expect the value of the event's outcome to be the result of the integral, but the value is calculated based on statistical probabilities.

Thanks again!
 
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