Approx. Probability of 20 Chips with Lifetime < 1.8M Hours in a Batch of 100

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SUMMARY

The discussion focuses on calculating the probability of finding at least 20 computer chips with lifetimes less than 1.8 million hours in a batch of 100 chips, where the lifetimes are normally distributed with a mean of 1.4 million hours and a standard deviation of 300,000 hours. The user, Rayne, correctly identifies the normal distribution parameters and calculates the probability of a single chip's lifetime being less than 1.8 million hours as approximately 0.9082. However, Rayne encounters difficulty in calculating the cumulative probability for the binomial approximation of the number of chips, leading to confusion about the continuity correction and the use of the normal approximation.

PREREQUISITES
  • Understanding of normal distribution and its parameters (mean and standard deviation).
  • Familiarity with binomial distribution and its properties.
  • Knowledge of continuity correction in statistical approximations.
  • Proficiency in using Z-scores for probability calculations.
NEXT STEPS
  • Learn about the Central Limit Theorem and its application in approximating binomial distributions.
  • Study the use of continuity correction in normal approximations of discrete distributions.
  • Explore statistical software tools like R or Python for performing binomial and normal probability calculations.
  • Investigate the implications of using normal approximations in real-world scenarios, particularly in quality control processes.
USEFUL FOR

This discussion is beneficial for statisticians, data analysts, and engineers involved in reliability testing and quality assurance of electronic components, particularly those working with lifetime data analysis of computer chips.

wu_weidong
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Hi all,
I need help with a problem.

The lifetimes of interactive computer chips are normally distributed with mean u = 1.4 * 10^6 hours and sigma = 3 * 10^5 hours. What is the approximate probability that a batch of 100 chips will contain at least 20 whose lifetimes are less than 1.8 * 10^6.

Here is what I did:

Let X be the lifetime of a chip, and Y be the number of chips whose lifetimes are less than 1.8 * 10^6.

X ~ N(1.4 * 10^6, (3 * 10^5)^2)
P(X < 1.8 * 10^6) = P(Z < ((1.8 * 10^6 - 1.4 * 10^6) / 3 * 10^5)) = P(Z < 1.33) = 0.9082

np = 100 * 0.9082 = 90.82
np(1-p) = 100 * 0.9082 * 0.0918 = 8.337
Y ~ N(90.82, 8.337)
Using normal distribution to approximate binomial distribution,
P(Y >= 20) = P(Y >= 19.5) (continuity correction) = P(Z >= ((19.5 - 90.82) / sqrt(8.337)) = P(Z >= -24.7)

At this point, I'm stuck, because I can't find a value for P(Z >= -24.7).

What have I done wrong?

Any help is appreciated. Thank you.

Regards,
Rayne
 
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Why even use a binomial approximation?
Let Y denote the number of computer chips whose lifetimes are less than 1.8*10^6. Then Y~Bin(100, 0.9082).
 
Because then I would have to calculate 20 terms of (100 C r)*(0.9082)^r * 0.0918^100-r --- from r = 0 to r = 19. I thought using an approximation would make the calculations much less tedious.
 
Last edited:

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