Proof for Mean-Mode=3(Mean-Median)

  • Thread starter Raghav Gupta
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In summary: Karl Pearson (I believe) developed that guideline (not a rule) from observations of many slightly to moderately skewed data sets and distributions. The equality you've written really should be taken as "approximately equal to", since the intent of the relationship was to have a quick way to approximate values. I don't know whether he published a derivation or simply mentioned it in an aside or lecture.
  • #1
Raghav Gupta
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Can anybody give proof of the above relationship algebraically?I have not seen the derivation of it.
 
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  • #2
I don't think that this is a generally valid relationship. I would guess that it holds for a PDF expressed in terms of a lowest order Edgeworth series.
 
  • #3
DrDu said:
I don't think that this is a generally valid relationship. I would guess that it holds for a PDF expressed in terms of a lowest order Edgeworth series.
I was in a hurry and when one is not familiar with the derivation ,often one messes the formula.
Yeah the correct relationship is Mode=3Median-2Mean.What is the derivation for it?
 
  • #4
That's the same formula you wrote before, only solved for Mode. It is not a general valid equation. For example, there are distributions which don't even have a mode, but a median and a mean.
I suppose you can get it using an Edgeworth expansion including the skewness and the curtosis:
http://en.wikipedia.org/wiki/Edgeworth_series
 
  • #8
I hardly know more about this relation than you. In the link I found there are all the references to original articles you need.
 
  • #9
DrDu said:
I hardly know more about this relation than you. In the link I found there are all the references to original articles you need.
I have seen that link in Mathematics stack exchange before and I did't get it that's why I have posted it here.When you first posted that it is not a valid relationship I thought that modification in statistic may have came for this formula.
 
  • #10
No problem if you don't know but if you can help for some initial steps It would help me.
 
  • #11
Karl Pearson (I believe) developed that guideline (not a rule) from observations of many slightly to moderately skewed data sets and distributions. The equality you've written really should be taken as "approximately equal to", since the intent of the relationship was to have a quick way to approximate values. I don't know whether he published a derivation or simply mentioned it in an aside or lecture.
 

1. What is the meaning of "Mean-Mode=3(Mean-Median)" in terms of proof?

"Mean-Mode=3(Mean-Median)" is a mathematical expression that represents a relationship between the mean, mode, and median of a set of data. It states that the difference between the mean and mode of a data set is three times the difference between the mean and median.

2. Is this equation always true for any data set?

No, this equation is not always true for any data set. It is a special case that only applies to certain data sets with specific characteristics.

3. How can this equation be useful in data analysis?

This equation can be useful in data analysis as it can provide insights into the distribution of the data. If the equation holds true for a data set, it suggests that the data may be skewed towards the mode. This can be helpful in identifying outliers or unusual data points.

4. Can this equation be used to find the mean, mode, or median of a data set?

No, this equation cannot be used to find the mean, mode, or median of a data set. It only represents a relationship between these three measures of central tendency.

5. Is there a way to prove this equation mathematically?

Yes, this equation can be proven mathematically using algebra and properties of the mean, mode, and median. The proof involves setting up equations for each measure of central tendency and manipulating them to show that they are equal to each other.

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