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705-805 (Hard)|   Graphs|                  
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parkhydel
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Here's another way to think about the second part of this question:

Take an example of a building with any roof height, let’s say 400 metres.

If the number of floors (black dot) is let’s say 80, then the mean height per floor (red dot) will be simply 400 divided by 80 = 5 metres.

If the number of floors (black dot) is let’s say 50, then the mean height per floor (red dot) will be simply 400 divided by 50 = 8 metres.

So it’s quite clear that there is a very sharp and clear inverse relationship between the black dos and the red dots, i.e., a strong negative correlation.
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To answer the first blank: The building with the greatest mean height per floor is represented by the uppermost black square on the graph. The horizontal coordinate of this square indicates that the roof height of the building is between 350 and 370 meters.

To answer the second blank: Now, this is relatively hard to answer. But we know what average is. It's the height of the net building divided by total number of floors. Isn't it? From the formula itself, we can determine that there is a negative correlation between number of floors and height of the building.
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We can see there is a positive correlation between the number of floors and height of the building’s roof, and there is a negative correlation between height of the building’s roof and the mean height per floor. Can I say it's a negative relationship between the number of floors and the mean height per floor?
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­1. The building with the greatest mean height per floor has a roof height between [350 and 370] meters.




2. There is a [Strong Negative] correlation between the number of floors and the mean height per floor.

­
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Gemmie
­1. The building with the greatest mean height per floor has a roof height between [350 and 370] meters.




2. There is a [Strong Negative] correlation between the number of floors and the mean height per floor.

­
Hi I have a quick question, I read somewhere that we remove outliers from the data and then compare correlation. If we remove the two black dots in top left of the graph. there seems to be no correlation b/w # of floors and mean hight per floor.
So should we remove the outliers or not?
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Can you define or clarify strong correlation? chetan2u Bunuel Bismuth83

In this question, I chose Negative, instead of strong negative, and I got 1 question wrong.
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Hi, the options provided are Strong Positive, Negligible, and Strong Negative. Do you mean Negligible?
Aalto700
Can you define or clarify strong correlation? chetan2u Bunuel Bismuth83

In this question, I chose Negative, instead of strong negative, and I got 1 question wrong.
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Aalto700
Can you define or clarify strong correlation? chetan2u Bunuel Bismuth83

In this question, I chose Negative, instead of strong negative, and I got 1 question wrong.
Most probably You have chosen 'negligible' as your answer. You may have got confused and that's normal. Negligible means no correlation, which suggests that there is no relationship between two variables.


the difference between strong negative and negative correlation is A negative correlation indicates two variables move in opposite directions—as one increases, the other decreases. A strong negative correlation simply means this inverse relationship is highly consistent and predictable, with data points tightly clustering together on a scatter plot
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it's standard practice to remove outliers, however on Gmat correlation is more about general trend, not strict mathematical rules.

if 1 or 2 outliers shows you different picture than general trend then you can ignore it. However if it supports general trend then no need to overthink about it.

Rex885

Hi I have a quick question, I read somewhere that we remove outliers from the data and then compare correlation. If we remove the two black dots in top left of the graph. there seems to be no correlation b/w # of floors and mean hight per floor.
So should we remove the outliers or not?
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