Chebyshev's Theorem Limit Question-Value Greater than 1

In summary, the conversation discusses the average amount of time that kids aged 12-17 spend watching TV, which is 3 hours per day with a standard deviation of 1 hour. The question asks what percentage of kids in this age group watch between 2 and 3 hours of TV per day. Using Chebyshev's inequality, the initial calculation results in 34%, but since the distribution is known to be bell-shaped, a more precise answer can be obtained using the cumulative normal distribution function.
  • #1
reemsh121
1
0

Homework Statement



According to Nielsen Media Research, kids ages 12-17 watch an average of 3 hours of tv per day. Suppose that the standard deviation is 1 hour and that the distribution of time spent watching tv has a bell-shaped distribution.

a) what percentage of kids aged 12-17 watch tv between 2 and 3 hours per day?


Homework Equations



1-1/z^2

The Attempt at a Solution



The standard deviation of 2 hours is 1, from the mean. But the value of z has to be greater than 1. With a question that has a range in it, usually means both sides will have a standard deviation from the mean. But one side is 1 and the other is the same as the mean.

So we only have one side, and I divided 1 in half to get .5 and plugged it into the formula.

1-1/.5^2

1-1/.25

1-4

-3

The answer is 34%.

I know I'm missing a step but I don't know what step. The formula is pretty straight forward and I get it, but this problem is really messing me up.
 
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  • #2
Chebyshev's inequality only makes a general statement about any probability distribution. So for example, if you plug in z = 1, you get 1-1/z^2 = 0, which means that no less than 0 of the values are more than 1 standard deviation away from the mean. But in this case, you know that the distribution is normal (a bell curve), so you can get a more precise answer, which is going to be the 34%.

As for how to get that 34%... look it up maybe? Or if you know the formula for the cumulative normal distribution (the error function), you can use that.
 
  • #3




I would like to clarify a few things about the problem and the attempted solution. Firstly, Chebyshev's theorem is used to calculate the percentage of data that falls within a certain number of standard deviations from the mean, not within a specific range. Secondly, the formula for Chebyshev's theorem is (1 - 1/z^2), where z is the number of standard deviations from the mean. In this case, z = 1, since we are looking at one standard deviation from the mean.

To answer the question, we can use the empirical rule, which states that approximately 68% of the data falls within one standard deviation from the mean, in a bell-shaped distribution. Therefore, approximately 68% of kids aged 12-17 watch tv between 2 and 3 hours per day. This aligns with the answer of 34% obtained in the attempted solution, as 34% is half of 68%.

In summary, Chebyshev's theorem is not applicable in this situation and the empirical rule should be used instead. It is important to understand the assumptions and limitations of different statistical tools and use them appropriately.
 

What is Chebyshev's Theorem?

Chebyshev's Theorem is a statistical theory that provides a mathematical measure of how much data falls within a certain number of standard deviations from the mean in any distribution.

How does Chebyshev's Theorem relate to limits?

Chebyshev's Theorem can be used to determine the proportion of data that falls within a certain distance from the mean, which can then be used to calculate the limit of the distribution.

Can Chebyshev's Theorem be used for any distribution?

Yes, Chebyshev's Theorem can be applied to any distribution, regardless of its shape or size. However, it is most useful for distributions with a large number of data points, as it is more accurate with larger sample sizes.

What is the formula for Chebyshev's Theorem?

The formula for Chebyshev's Theorem is:

P(|X-μ| ≥ kσ) ≤ 1/k²

Where X is the random variable, μ is the mean, σ is the standard deviation, and k is the number of standard deviations from the mean.

How can Chebyshev's Theorem be used to find the probability of a value greater than 1 standard deviation from the mean?

By plugging in the values of the mean, standard deviation, and k=1 into the formula for Chebyshev's Theorem, we can calculate the probability of a value being greater than 1 standard deviation from the mean. This will give us an upper bound for the proportion of data that falls within 1 standard deviation from the mean.

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