Chebyshev's Inequality Problem

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In summary, the conversation discussed using Chebyshev's inequality to estimate the probability of the absolute value of a uniformly distributed random variable being greater than or equal to 1. The formula for Chebyshev's inequality was used, along with the variance formula for a uniform RV, to arrive at an estimated probability of 4/3. The exact value was also calculated using the cumulative distribution function of a uniform RV, resulting in a probability of 0.25. The accuracy of the estimated probability was then questioned and further steps were discussed to verify the calculation.
  • #1
clipperdude21
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Let X be uniformly distributed over (-2,2). Use Chebyshev's inequality to estimate P(abs(x) >= 1) and compare to the exact value.

The answer in the book got something different than what i got so i wanted to see if i was rightEX of a uniformly distrubuted RV is (a+b)/2 so -2+2/0 =0
So i plugged into the formula.

P(abs(x)>=1 <= sigma^2

the variance of a uniformly RV is (b-a)^2/12 so (2-(-2))^2=14 and 14/12 is 4/3.

my first answer ======= P(abs(x)>=1 <= 4/3For the exact part I used the P(X<=x) cdf of a unform RV and got F(1)=3/4. So 1-F(1) = 0.25 which is the probability we are looking for.Did i do this right? Thanks!
 
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  • #2
Write out Cheb's Ineq. and walk through the steps.
 
  • #3


Yes, you have correctly applied Chebyshev's inequality to estimate the probability P(abs(x) >= 1) and your answer of 4/3 is correct. However, the exact value for this probability is actually 1/2, which is different from the answer in the book. This means that Chebyshev's inequality provides a conservative estimate for this particular problem.
 

Related to Chebyshev's Inequality Problem

What is Chebyshev's Inequality Problem?

Chebyshev's Inequality Problem is a mathematical concept that describes the relationship between the mean, median, and standard deviation of a set of data. It is used to determine the likelihood of a certain number of data points falling within a certain distance from the mean.

How is Chebyshev's Inequality Problem used?

Chebyshev's Inequality Problem is used to calculate the probability of a certain number of data points falling within a certain distance from the mean, regardless of the shape of the data distribution. This allows for a more accurate understanding of the data and its spread.

What is the formula for Chebyshev's Inequality Problem?

The formula for Chebyshev's Inequality Problem is P(|x - μ| ≥ kσ) ≤ 1/k², where P is the probability, x is the data point, μ is the mean, σ is the standard deviation, and k is the number of standard deviations from the mean.

What are the assumptions of Chebyshev's Inequality Problem?

The assumptions of Chebyshev's Inequality Problem are that the data set is independent, the mean and standard deviation are known, and the data set is large enough to be representative of the entire population.

What are the limitations of Chebyshev's Inequality Problem?

Chebyshev's Inequality Problem is limited by its assumption of a large and representative data set, as well as its inability to provide precise probabilities for specific data points. It also assumes that the data set is continuous and symmetric, which may not always be the case.

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