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ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Determining The Statistical Measures On Student's Performance Metrics Using Python Code

Authors: Dr Preetha V;

Determining The Statistical Measures On Student's Performance Metrics Using Python Code

Abstract

This research investigates the student's performance metrics using statistical measures based on the dataset. Students studies and achievements have been distracted by various factors such as sleeping hours, internet access, motivational level and other environmental factors. The study of this research will be helpful to find the exact reasons for the performance of the students. Further, this research focusses on the python coding using pandas library to find the statistical measures. The research explored various datasets and find the best suitable dataset with 6000 entries for the exact analysis.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green