Скачать или смотреть Unbiasedness of Sample Variance (s²) in SRSWOR | Statistics B.Sc. Concept Explained

In this video, we prove that the sample mean sum of squares (s²) is an unbiased estimator of the population mean sum of squares (S²) under Simple Random Sampling Without Replacement (SRSWOR).

This is an important concept in Sampling Theory, commonly asked in B.Sc. Mathematics & Statistics exams, competitive exams like NET, GATE, and UPSC (CDS/IAS optional subjects).

👉 What you will learn in this video:

Concept of unbiasedness in statistics

Proof that sample variance (s²) is an unbiased estimator of population variance (S²)

Application in SRSWOR (Simple Random Sampling Without Replacement)

Step-by-step mathematical explanation


Perfect for undergraduate students, exam preparation, and self-study learners.


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🔑 Keywords:

unbiased estimator, sample variance, population variance, s² unbiased estimator, S² population variance, sampling theory, statistics BSc, SRSWOR, simple random sampling without replacement, unbiasedness proof, estimation in statistics, statistics exam preparation, B.Sc. mathematics statistics, CDS statistics preparation, GATE statistics


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🏷️ Hashtags:

#Statistics #SamplingTheory #SRSWOR #UnbiasedEstimator #SampleVariance #BScMathematics #StatisticsLecture #ExamPreparation