Tsebyshev's probability

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In summary, using Tsebyshev's inequality, it can be determined that the lower bound for the probability that a product lasts at least 5 years is approximately 0.974. However, in the given problem, the calculation error of squaring the variance resulted in an incorrect answer. The correct probability is approximately 0.973.
  • #1
TheSodesa
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Homework Statement


The average lifetime of a product ##T=7.5## (years). The variance of the lifetime ##\sigma^{2} = 0.41##.

Using Tsebyshev's inequality, determine the lower bound for the probability, that the product lasts at least 5 years.

Homework Equations



Tsebyshev's inequality:
\begin{equation}
P(|X-\mu | \geq t) \leq \frac{\sigma^{2}}{t^2}
\iff
P(|X-\mu | < t) \geq 1 - \frac{\sigma^{2}}{t^2}
\end{equation}
where ##\mu## is the expected value, ##\sigma^2## is the variance and ##t## is the deviation from the expected value.

The Attempt at a Solution



We want
\begin{align*}
P(T \geq 5)
&\geq P(5 \leq T \leq 10)\\
&= P(|T-7.5| \leq 2.5) &|t=2.5\\
&\geq 1 - \frac{\sigma^2}{t^2} &| Tsebyshev\\
&= 1-\frac{0.41^2}{2.5^2}\\
&\approx 0.973
\end{align*}
This is apparently not the correct answer, and I'm not sure what I'm doing wrong. We obviously want the deviation from the mean to be less than 2.5; otherwise ##|T-\mu|## would produce a value that is below 5.
 
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  • #2
Edit: Why did you square the 0.41?

Some manual tuning: The worst case is some fraction p failing "just before" 5 years and all other machines failing after X years, X a bit larger than 7.5

The condition for the mean is then 5p+(1-p)*X = 7.5.
The condition for the variance is p*2.5^2 + (1-p)*(X-7.5)^2 = 0.41

Solving gives p=0.062 and X=7.66.
 
Last edited:
  • #3
mfb said:
Why do you think the answer is wrong?

You can use it for both. One gives a lower bound, the other gives an upper bound.
 
  • #4
TheSodesa said:

Homework Statement


The average lifetime of a product ##T=7.5## (years). The variance of the lifetime ##\sigma^{2} = 0.41##.

Using Tsebyshev's inequality, determine the lower bound for the probability, that the product lasts at least 5 years.

Homework Equations



Tsebyshev's inequality:
\begin{equation}
P(|X-\mu | \geq t) \leq \frac{\sigma^{2}}{t^2}
\iff
P(|X-\mu | < t) \geq 1 - \frac{\sigma^{2}}{t^2}
\end{equation}
where ##\mu## is the expected value, ##\sigma^2## is the variance and ##t## is the deviation from the expected value.

The Attempt at a Solution



We want
\begin{align*}
P(T \geq 5)
&\geq P(5 \leq T \leq 10)\\
&= P(|T-7.5| \leq 2.5) &|t=2.5\\
&\geq 1 - \frac{\sigma^2}{t^2} &| Tsebyshev\\
&= 1-\frac{0.41^2}{2.5^2}\\
&\approx 0.973
\end{align*}
This is apparently not the correct answer, and I'm not sure what I'm doing wrong. We obviously want the deviation from the mean to be less than 2.5; otherwise ##|T-\mu|## would produce a value that is below 5.

You are given ##\sigma^2 = 0.41##. But later on, you write ##0.41^2## at the end of your computation. There is no need for that square.
 
  • #5
mfb said:
Chebyshev's inequality makes a statement about larger deviations. You can use it for P(|T-7.5|>2.5) but not for P(|T-7.5|<2.5).

So what I could do is calculate ##P(T<5)## and go from there?

\begin{align*}
P(T<5)
&\leq P(T<5 \text{ and } T>10)\\
&= P(|T-\mu| >= 2.5)\\
&\leq \frac{\sigma^2}{2.5^2}\\
&=\frac{0.41^2}{2.5^2}\\
&= 0.026896
\end{align*}
But then I'm stuck with the shaded area shaded blue in this picture:
S3_4.png

and I need the one in the middle. At least that's my understanding.
 
  • #6
micromass said:
You are given ##\sigma^2 = 0.41##. But later on, you write ##0.41^2## at the end of your computation. There is no need for that square.

Oh. My. Gauss!

Thank you. How typical of me...
 

Related to Tsebyshev's probability

1. What is Tsebyshev's probability?

Tsebyshev's probability, also known as Chebyshev's inequality or Chebyshev's theorem, is a mathematical concept that describes the likelihood of a random variable deviating from its expected value. It provides an upper bound on the probability of the random variable being a certain distance away from its expected value.

2. How is Tsebyshev's probability calculated?

The formula for Tsebyshev's probability is P(|X-μ| ≥ kσ) ≤ 1/k^2, where X is the random variable, μ is the expected value, σ is the standard deviation, and k is the number of standard deviations from the mean.

3. What is the significance of Tsebyshev's probability?

Tsebyshev's probability is important in statistics because it provides a way to measure the dispersion of data around the mean. It is also used in probability theory to determine how likely it is for a random variable to be a certain distance away from its expected value.

4. Can Tsebyshev's probability be used in real-world situations?

Yes, Tsebyshev's probability can be applied to real-world situations where data is collected and analyzed. For example, it can be used in finance to predict the likelihood of a stock price deviating from its expected value, or in quality control to determine the probability of a product being a certain distance away from its desired specifications.

5. Are there any limitations to Tsebyshev's probability?

While Tsebyshev's probability is a useful tool, it does have some limitations. It assumes that the data is normally distributed and that there are no outliers. It also provides a very broad estimate of the probability and does not take into account the shape of the distribution. Other techniques, such as the Central Limit Theorem, may be better suited for certain scenarios.

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