Chebyshev's Theorem: Decision for Lumber Buyer

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In summary, the buyer's decision should be not to purchase the land based on the mean and standard deviation of the tree heights provided.
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A buyer for a lumber company must decide whether to buy a piece of land containing 5,000 pine trees. If 1,000 of the trees are at least 40 feet tall, the buyer will purchase the land; otherwise, he won't. The owner of the land reports that the height of the trees has a mean of 30 feet and a standard deviation of 3 feet. Based on this information, what is the buyer's decision?





Homework Equations



By Chebyshev’s Theorem (1-1/K2 )

The Attempt at a Solution



By Chebyshev’s Theorem (1-1/K2 )
1000/5000= 1/5 = 1-1/K2 so
1/K2 = 1-1/5 = 4/5 so

K = 1.118, so

20% fall between 26.646 and 33.354


So I advise against .

Is this right?
 
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  • #2
The buyer should not purchase the land because there is only a 20% chance that at least 1,000 of the trees are 40 feet tall.
 
  • #3


I would suggest that the buyer use Chebyshev's Theorem as a guideline, but also consider other factors such as the cost of the land and potential profits from the trees. Chebyshev's Theorem gives a general estimate of the proportion of trees that are at least 40 feet tall, but it does not take into account potential outliers or other factors that may affect the decision. It would be beneficial for the buyer to conduct further research and analysis before making a final decision.
 

1. What is Chebyshev's Theorem?

Chebyshev's Theorem, also known as the Chebyshev's Inequality, is a statistical theorem that provides a way to estimate the proportion of values within a certain distance from the mean of a dataset. It is used to make decisions in various fields, including economics and finance.

2. How does Chebyshev's Theorem help in decision making for a lumber buyer?

Chebyshev's Theorem can help a lumber buyer make decisions by providing a way to estimate the proportion of lumber that falls within a certain distance from the mean length. This can help the buyer determine the quality and value of the lumber, and make informed decisions about purchasing.

3. What is the formula for Chebyshev's Theorem?

The formula for Chebyshev's Theorem is: P(|X - μ| ≥ kσ) ≤ 1/k^2, 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.

4. Can Chebyshev's Theorem be used for any dataset?

Yes, Chebyshev's Theorem can be used for any dataset, regardless of its distribution. However, it is most useful for data that follows a bell-shaped curve, such as a normal distribution.

5. Are there any limitations to using Chebyshev's Theorem?

While Chebyshev's Theorem is a useful tool, it has some limitations. It only provides an estimate of the proportion of values within a certain distance from the mean, and does not give specific values. Additionally, it assumes that the mean and standard deviation of the dataset are known, which may not always be the case.

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