Solving Chebyshev's Inequality with 900 Coin Flips - 35/36 Probability

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In summary, the conversation discusses the use of Chebyshev's inequality to verify the probability of the proportion of heads in 900 flips of a balanced coin falling between 0.40 and 0.60. The conversation also mentions the formula for E(Y) and variance(Y) and how to calculate the expected number of heads and standard deviation in this scenario. The conversation concludes by discussing the number of standard deviations from the mean and how it relates to 1/k2 in Chebyshev's theorem.
  • #1
Gémeaux
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Hi.

I'm having a bit of trouble with Chebyshev's inequality and I was wondering if someone could point me in the right direction as to how to answer this question:

Use chebyshev's theorem to verify that the probability is at least 35/36 that in 900 flips of a balanced coin the proportion of heads will be between 0.40 and 0.60.

By the looks of it, I have to use E(Y)=p, variance(Y)=p(1-p)/n.

I'm not quite sure how to approach this as my lecturer didn't cover this in much depth.

Thank you.
 
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  • #2
Do you at least know what Chebyshev's theorem says?
 
  • #3
Do you at least know what Chebyshev's theorem says?

My understanding of it is "For any population or sample, at least (1 - (1 / k)2) of the observations in the data set fall within k standard deviations of the mean, where k greater than or equal to 1."

Okay, for 900 flips of an unbiased coin what will the expected number of heads be? (No, it is not p, it is E(Y)=pn. And p= ? n= ?). What will the standard deviation be? (yes, the variance is variance(Y)=p(1-p)/n. And so the standard deviation is?

Now that you have figured out what the mean and standard deviation for this problem are, the proportion of head in 900 flips between .4 and .6 means that the actual number of heads is what? How far on either side of the mean are those? How many standard deviations (k) is that? Finally, what is 1/k2?
 

What is Chebyshev's Inequality?

Chebyshev's Inequality is a mathematical formula that provides a way to estimate the probability that a random variable will fall within a certain number of standard deviations from its mean. It is often used in statistics to understand the spread of data and to make predictions about the likelihood of events occurring.

How does Chebyshev's Inequality relate to 900 coin flips with a probability of 35/36?

In the context of 900 coin flips with a probability of 35/36, Chebyshev's Inequality can be used to determine the likelihood of getting a certain number of heads or tails. It allows us to estimate the probability of getting results that deviate from the expected outcome.

What is the significance of 900 coin flips in this scenario?

900 coin flips is a large enough sample size to apply Chebyshev's Inequality. As the sample size increases, the probability of getting results that deviate from the expected outcome decreases. In this case, 900 coin flips allows us to make more accurate predictions about the likelihood of getting a certain number of heads or tails.

What is the role of probability in solving Chebyshev's Inequality with 900 coin flips?

Probability is a key component of Chebyshev's Inequality. The formula uses the probability of an event occurring, in this case 35/36, to calculate the likelihood of getting results that deviate from the expected outcome. The higher the probability, the less likely it is that the results will deviate significantly.

How can Chebyshev's Inequality be applied in other scenarios?

Chebyshev's Inequality can be applied in various scenarios, such as in finance to estimate the likelihood of stock prices deviating from their expected value, or in quality control to predict the likelihood of defects in a manufacturing process. It is a versatile formula that can be used in a wide range of fields to make predictions and understand the spread of data.

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