Statistical Moments: Mean, Variation, Skewness, Kurtosis скачать в хорошем качестве

Statistical Moments: Mean, Variation, Skewness, Kurtosis

Relying only on averages can hide the real story in your data. In this video, we explain why the mean isn’t enough and show how standard deviation, skewness, and kurtosis reveal hidden patterns, outliers, and risks that averages completely miss. Perfect for anyone learning statistics, data analysis, or data science. Related Videos ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Bayesian Optimization:    • Bayesian Optimization   Hyperparameters Tuning: Grid Search vs Random Search:    • Hyperparameters Tuning: Grid Search vs Ran...   The Kernel Trick:    • The Kernel Trick   Cross-Entropy - Explained:    • Cross-Entropy - Explained   Dropout - Explained:    • Dropout in Neural Networks - Explained   Overfitting vs Underfitting:    • Overfitting vs Underfitting - Explained   Why Models Overfit and Underfit - The Bias Variance Trade-off:    • Bias-Variance Trade-off - Explained   Least Squares vs Maximum Likelihood:    • Least Squares vs Maximum Likelihood   XGBoost Explained in Under 3 Minutes:    • XGBoost Explained in Under 3 Minutes   Contents ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 00:00 - Intro 00:26 - Example 00:59 - The mean 01:17 - The standard deviation 01:45 - The skewness 02:16 - The kurtosis 03:10 - Outro Follow Me ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🐦 Twitter: @datamlistic   / datamlistic   📸 Instagram: @datamlistic   / datamlistic   📱 TikTok: @datamlistic   / datamlistic   👔 Linkedin:   / datamlistic   Channel Support ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ The best way to support the channel is to share the content. ;) If you'd like to also support the channel financially, donating the price of a coffee is always warmly welcomed! (completely optional and voluntary) ► Patreon:   / datamlistic   ► Bitcoin (BTC): 3C6Pkzyb5CjAUYrJxmpCaaNPVRgRVxxyTq ► Ethereum (ETH): 0x9Ac4eB94386C3e02b96599C05B7a8C71773c9281 ► Cardano (ADA): addr1v95rfxlslfzkvd8sr3exkh7st4qmgj4ywf5zcaxgqgdyunsj5juw5 ► Tether (USDT): 0xeC261d9b2EE4B6997a6a424067af165BAA4afE1a #statistics #datascience #analytics #machinelearning