Data Science and A.I. – Quartiles, Deciles, and Percentiles

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1 PostNetwork Academy guides us through three crucial statistical measures: Quartiles, Deciles, and Percentiles
1.1 Quartiles
1.2 Deciles
1.3 Percentiles
1.4 Video
1.5 PDF Presentation
1.6 Conclusion
1.7 See Also:

PostNetwork Academy guides us through three crucial statistical measures: Quartiles, Deciles, and Percentiles

These measures are used to divide a data distribution into equal parts, making them essential tools in data analysis.

Hello everyone! Welcome to another educational post from PostNetwork Academy. I’m Bindeshwar, and before we begin, make sure to follow us on all our social media platforms: YouTube, Facebook, and LinkedIn. This way, you’ll stay updated with all our latest content. And don’t forget to visit our website at www.postnetwork.co for more in-depth articles and resources.

Today, we are discussing Quartiles, Deciles, and Percentiles—three statistical measures that help divide a distribution into equal parts.

Quartiles

Quartiles are the values that divide the distribution into four equal parts. There are three quartiles in total, and they are denoted as Q1, Q2, and Q3.

The formula for Q1 is:

Q1 = (n + 1) / 4th observation.

This means that 25% of the data falls below Q1, and 75% lies above it. Q2 is the median, and 50% of the data falls both above and below Q2. The formula for Q2 is:

Q2 = (n + 1) / 2th observation.

If the number of observations is odd, Q2 is the middle value, and if it’s even, Q2 is the average of the two middle values.

Moving on to Q3, it marks the 75th percentile, meaning 75% of the data lies below Q3 and 25% above. The formula for Q3 is:

Q3 = 3 × Q1

Deciles

Deciles divide the distribution into 10 equal parts, so there are nine deciles in total. The formula for any decile Di is:

Di = (i(n + 1)) / 10th observation, where i is from 1 to 9.

For example, D1 is the first decile, which represents the 10th percentile, and so on.

Percentiles

Finally, we come to Percentiles, which divide the data into 100 equal parts. There are 99 percentiles in total, and their formula is similar to the one used for deciles:

Pi = (i(n + 1)) / 100th observation, where i is from 1 to 99.

For instance, P1 is the first percentile, representing 1% of the data.

Video

 

PDF Presentation

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Conclusion

That concludes our discussion on Quartiles, Deciles, and Percentiles. I hope this breakdown helps you understand how these measures work and how you can apply them to your data. In future videos, I’ll be covering numerical examples to make these concepts clearer.

If you found this video helpful, please give it a thumbs up, share it with your friends, and let us know in the comments what topics you’d like us to cover next. Thanks for watching, and see you in the next video!

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See Also:

  1. What is Weighted Mean?
  2. Data Science and A.I. : Measures of Dispersion : Variance of Continuous Freq. Distribution
  3. Latex Code for Data Science and A.I. : Measures of Dispersion : Variance of Continuous Freq. Distribution
  4. Understanding Variance in Data Science and AI and ML
  5. Data Science and A.I.: Measures of Dispersion – Variance of Continuous Frequency Distribution
  6. Understanding Key Properties of the Arithmetic Mean: A Dive for Data Science Enthusiasts
  7. Median in Data Science and AI
  8. Data Science and A.I. : Measures of Dispersion : Variance of Continuous Freq. Distribution
  9. Data Science and A.I. – Measures of Dispersion: Variance of Discrete Frequency Distribution
  10. Data Science and A. I. : : Measures of Dispersion :: Variance of Discrete Frequency Distribution
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