Probability of Hypokalemia w/ 1 or Multiple Measurements

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The discussion focuses on calculating the probability of hypokalemia based on potassium measurements. For a single measurement, the probability of a patient being diagnosed as hypokalemic (potassium levels below 3.5 mmol/L) is approximately 0.0668, derived from the standard normal distribution. When considering four separate measurements, the probability of a diagnosis depends on how many of those measurements fall below the threshold, with calculations suggesting a probability around 0.00113. There is confusion regarding the criteria for diagnosis based on multiple samples, specifically whether at least one or all must be positive for hypokalemia. Clarification on the interpretation of multiple measurements is needed to accurately determine the diagnosis probability.
SakuRERE
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Misplaced Homework Thread moved from the technical forums
TL;DR Summary: Finding the probability with one measurement and multiple measurements on separate days.

Question: Hypokalemia is diagnosed when blood potassium levels are low, below 3.5 mmol/L. Let’s assume we know a patient whose measured potassium levels vary daily according to N(µ = 3.8 mmol/L, σ = 0.2 mmol/L).
(a) If a single potassium measurement is made, what is the probability that the patient is diagnosed as hypokalemic?
(b) If measurements are made instead on 4 separate days, what is the probability that the patient is diagnosed with hypokalemia?

For part A -->

I solved the question as a standardized normal distribution. I tried to find P(x<=3.5),
using the standard normal formula z= X-Mean/SD I converted the X value 3.5 to a Z score and got P(x<=-1.5)
after that, I used the Gauss table to find the probability and it was P(x<=-1.5)= 0.0668
this answer was similar to the answer key provided by our professor.

However, for the second part, the answer key has to be 0.0013 but I can't think of a way to figure it out. And I don't understand how taking different measurements on separate days will influence my probability.
I will appreciate your help, thank you!

I attached the positive and negative Gauss tables for easier accessibility.
 

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What does it even mean to be diagnosed after 4 samples? Do you have to get at least one positive? All positive?

The odds of getting more positives than negatives are
##4(.0668)^3(1-.0668)+.0668^4\approx 0.00113## which is not that far from what the answer key says...
 
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Or an average of the four below 3.5?
Some more information is needed in the problem statement.
 
Office_Shredder said:
What does it even mean to be diagnosed after 4 samples? Do you have to get at least one positive? All positive?

The odds of getting more positives than negatives are
##4(.0668)^3(1-.0668)+.0668^4\approx 0.00113## which is not that far from what the answer key says...
Thanks for replying
But I didn’t get what’s that formula you used

Thanks again
 
SakuRERE said:
Thanks for replying
But I didn’t get what’s that formula you used

Thanks again
I added the odds of getting three positives and of getting four positives.

I have no reason to think that's what they want you to do other than the similarity of the answer.
 
First, I tried to show that ##f_n## converges uniformly on ##[0,2\pi]##, which is true since ##f_n \rightarrow 0## for ##n \rightarrow \infty## and ##\sigma_n=\mathrm{sup}\left| \frac{\sin\left(\frac{n^2}{n+\frac 15}x\right)}{n^{x^2-3x+3}} \right| \leq \frac{1}{|n^{x^2-3x+3}|} \leq \frac{1}{n^{\frac 34}}\rightarrow 0##. I can't use neither Leibnitz's test nor Abel's test. For Dirichlet's test I would need to show, that ##\sin\left(\frac{n^2}{n+\frac 15}x \right)## has partialy bounded sums...

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