なぜn-1で割るのか？がわかる！標本分散と不偏分散の違いと使い分けを徹底解説！

This time, we'll clearly explain the difference between sample variance and unbiased variance, and why unbiased variance is calculated by dividing the sum of squares by n-1. It's often misunderstood that "unbiased variance is the correct answer when calculating variance," but there are situations where sample variance and unbiased variance are appropriate, and it's important to properly distinguish between them. This video will also be useful for studying for the QC certification exam. We'll continue to provide helpful videos, so we appreciate your support (^-^) =============================================== [Related Videos] ▼Central Limit Theorem. This is one of the reasons normal distributions often appear in statistics!    • 中心極限定理。統計学で正規分布がよく出てくる理由のひとつがこれ！   ▼[Exam Preparation] Reduce calculation time with the variance formula! [Proof]    • 【試験対策】分散の公式で計算時間短縮！［証明］   ▼We conducted a simulation to verify whether unbiased variance is truly "unbiased."    • 不偏分散が本当に『不偏性』を持つのかシミュレーションで確かめてみた。   ===================================================== Subscribe to the channel here ☞   / @datasciencelab.   #QC Certification Level 1 Outstanding Achievement Award Winner Comments