Inverse cumulative normal dis help

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Discussion Overview

The discussion revolves around solving for the variable k in the context of a probability question involving a normally distributed random variable X, specifically under the condition Pr(X

Discussion Character

  • Mathematical reasoning, Technical explanation, Homework-related

Main Points Raised

  • One participant seeks assistance in solving for k in the equation Pr(X
  • Another participant notes that if k is greater than or equal to 23, then P(X
  • It is suggested that if k is less than 23, the conditional probability can be expressed as P(X
  • A later reply mentions that a book provides the answer as 17.525, indicating a potential solution but not confirming its correctness.
  • One participant asks for clarification on the notation X-N(22,25), requesting a verbal expression of what it represents.

Areas of Agreement / Disagreement

Participants have not reached a consensus on the solution for k, and multiple viewpoints regarding the conditional probability and notation remain present.

Contextual Notes

The discussion includes unresolved questions about the assumptions underlying the conditional probability and the interpretation of the notation used.

bayan
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any one know how to solve for [tex]k[/tex] in the following question?

[tex]Pr(X<k|X<23)=0.32[/tex] where [tex]X-N(22,25)[/tex].

I just can't get it.

cheers n thanks in advance.
 
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P(X<k|X<23) = 1 if k >= 23 why??
if k<23, then
P(X<k|X<23) = P(X<k)/P(X<23) why??

-- AI
 
doesn't work out and they have the answer as 17.525 in book.

any helps
 
What does this notation mean: [itex]X-N(22,25)[/itex] ? Can you express it with words?
 

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