Unbiasedness of Sample Variance (s²) in SRSWOR | Statistics B.Sc. Concept Explained
Автор: Statistics Perfection
Загружено: 2025-08-24
Просмотров: 20
Описание:
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
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