10.21 Bessel’s Correction | Why n-1 in sample variance? | Statistics & Probability

Описание: In this video, we explore why we divide by (n–1) instead of n when calculating sample variance. You’ll understand the intuition behind Bessel’s Correction, how it removes bias in estimating population variance, and why it gives a more accurate measure of data spread. This Statistics & Probability playlist is also helpful for GATE DA/CS and other streams.

📌 Topics Covered in this Video:
1. Population vs Sample Variance – Explained Intuitively
2. Limitation of calculating variance using n
3. Introduction to Bessel’s Correction – Why do we need it?
4. Why we use (n–1) instead of n for computing sample variance
5. How Bessel’s Correction ensures an unbiased estimate of population variance

Helpful For:
1. Cracking AI / ML / Data Science interview rounds at top tech companies
2. Building a deeper understanding of core AI, ML concepts
3. Preparing for GATE (DA / CS / Other streams) and other related competitive exams

Our Playlist:
Probability & Statistics for ML - Hindi:    • 10. Probability & Statistics for ML  

#BesselsCorrection #SampleVariance #PopulationVariance #StatisticsInHindi #MachineLearning #StatisticsForML #InferentialStatistics #UnbiasedEstimator #WhyNMinus1 #DataScienceInHindi #StatisticsTutorial #statisticsforbeginners

Tags:
Bessel’s correction, why n - 1 in sample variance, sample variance vs population variance, statistics in hindi, population variance explained, sample variance explained, statistics for ml, population and sample variance, unbiased variance estimation