Expected Value of Distribution on Histogram: T/F

In summary, the expected value of a distribution does not always occur at the center of the tallest bar on the histogram, as it can be definite or indefinite. To confirm this, one can calculate the mean value of the histogram and check if it falls within the highest bar. Making a histogram and testing it is an easy way to settle this and avoid guessing. This can be done using Matlab or even by hand.
  • #1
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Homework Statement



4: (T/F) The expected value of a distribution always occurs at the center of the tallest bar on the histogram.

Homework Equations



(no equation necessary for it is T/F)

The Attempt at a Solution



I believe this is false for the expected value can be definite or indefinite.
 
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  • #2
If you believe it is false, why don't you make a simple histogram that illustrates that it isn't true? That would settle it and you wouldn't be guessing.
 
  • #3
Yup, just make up a histogram and test it.
Easy as pie in Matlab, or even just by hand.

-> The thing to do is calculate the mean value of the histogram, and check if that is in the "highest bar".
 

1. What is the expected value of a distribution on a histogram?

The expected value of a distribution on a histogram is the average value that would be obtained if the experiment were repeated an infinite number of times. It represents the center of the distribution and is calculated by multiplying each possible outcome by its probability and summing all of the products.

2. How is the expected value of a distribution on a histogram calculated?

The expected value of a distribution on a histogram is calculated by multiplying each possible outcome by its probability and summing all of the products. This can be represented by the formula E(X) = ∑xP(x), where x is each outcome and P(x) is the probability of that outcome.

3. Is the expected value of a distribution on a histogram always a possible outcome?

No, the expected value of a distribution on a histogram may not always be a possible outcome. It is a calculated value that represents the average of all possible outcomes, but it does not necessarily have to correspond to an actual outcome.

4. How does the expected value of a distribution on a histogram relate to the shape of the histogram?

The expected value of a distribution on a histogram can give insight into the shape of the histogram. If the expected value is closer to the left side of the histogram, it indicates a left-skewed distribution. If it is closer to the right side, it indicates a right-skewed distribution. If it is in the center, it indicates a symmetrical distribution.

5. Can the expected value of a distribution on a histogram be negative?

Yes, the expected value of a distribution on a histogram can be negative. This can occur when there are negative outcomes in the distribution, or when the distribution is heavily skewed towards the negative side. It is important to consider the context of the data when interpreting a negative expected value.

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