📊 Data Analytics for Beginners | Descriptive Statistics Explained with Python | Class 1 by Subir Das

📜 YouTube Description

🎓 Data Analytics Class 1 — Understanding Numbers Like a Data Scientist!

Welcome to Class 1 of the Data Analytics Series, where we explore how to analyze and describe data like real data scientists using Descriptive Statistics and Python.

This beginner-friendly class is perfect for anyone who wants to build a solid foundation in data interpretation before diving into advanced analytics and machine learning.


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📘 What You’ll Learn

Mean, Median & Mode — measures of central tendency

Standard Deviation — understanding variability

Quantiles & Percentiles — ranking your data

Boxplot — visualizing data spread and outliers

Python implementation using NumPy, Matplotlib & Statistics


📊 Example Used:
A simple student marks dataset — easy to understand and practically relatable.


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💡 Why Learn This

If you’ve ever wondered “How do analysts summarize and interpret raw data?” — this class breaks it down step by step.
You’ll learn to think like an analyst and apply your learning with real Python code.


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💻 Sample Python Snippet

import numpy as np
np.mean([40,50,60,70,80])
np.median([40,50,60,70,80])
import statistics
statistics.mode([50,60,60,70,80])


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🚀 Next Class

Data Visualization — Histograms & Scatter Plots

📅 Upcoming Live Session:
🎓 Beginner Friendly | Free Live Class | October 26
📞 Contact: 9609378011 to join


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👨‍🏫 Instructor: Subir Das

M.Sc. (Mathematics) | M.Tech (ISI Kolkata)
JRF Qualified in Mathematics
Data Analytics & Credit Risk Expert
Specialized in Statistical Modeling, SAS, and Python for Analytics


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📌 Hashtags

#DataAnalytics #StatisticsForBeginners #PythonForDataScience #SubirDas #LearnDataAnalytics #DescriptiveStatistics #Boxplot #MeanMedianMode #DataVisualization #Unibask #LearnWithSubir


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