Interpeting data figures - its rather simple but not soo simple

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Interpreting skewness using quartiles involves comparing the distances between Q1, Q2, and Q3 to determine the distribution's shape. A negative skew indicates that Q2 - Q1 is greater than Q3 - Q2, suggesting that data values are generally smaller. Conversely, a positive skew occurs when Q3 - Q2 is greater than Q2 - Q1, indicating larger data values. Understanding that 25% of data lies below Q1, 50% around the median, and 75% below Q3 is crucial for analysis, but the actual values of Q1 and Q3 can vary between samples. This knowledge allows for a more nuanced interpretation of data sets in various contexts.
SavvyAA3
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Can Someone please tell me how I can interpret the skewness of a distribution using quartiles.

I know that if Q2 – Q1 > Q3 – Q2 : Negative skew and if Q3 – Q2 > Q2 – Q1: Positive Skew and if Q2 –Q1 = Q3 – Q1: Symmetrical data dispersion

What I really need to know is how to use the above to interpret data sets and be able to apply it to all situations. I’ve never really been able to say more than the above in GCSE and A-level and this got me an A in math at both stages but at Uni I really need to interpret this stuff.

Can I say that if the data is negatively skewed then the data values tend to be generally very small? What confuses me is that we will always have 25% of the data lying below Q1 and 50% of the data lying either side of the median and 75% below Q3. But how can we use this to give analysis??

Thanks.
 
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SavvyAA3 said:
What confuses me is that we will always have 25% of the data lying below Q1 and 50% of the data lying either side of the median and 75% below Q3. But how can we use this to give analysis??
That is correct; but the data values of Q1 and Q3 will differ from one sample to the other.
 
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