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Curated by: Khan Academy India - English (13 videos)
In this video, we investigate the effect of shifting data (adding a constant 'a' to each observation) on its mean, variance, and standard deviation. We will prove that while the mean shifts by the constant 'a' (i.e., new mean equals old mean plus 'a'), the variance of the dataset remains unchanged. This means the standard deviation also stays the same, as shifting data points doesn't alter their spread. Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now! (https://www.khanacademy.org/math/ncert-class-11/xea4762213f311c5e:statistics-ncert-new/xea4762213f311c5e:variance-and-standard-deviation/e/standard_deviation_of_a_population) Timestamps: 00:00 Problem: Effect of shifting data on Variance and SD 03:04 Proof: How the mean changes when data is shifted by 's' (new mean = old mean + s) 04:21 Proof: Variance remains unchanged when data is shifted by 's' Khan Academy India is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We have videos and exercises that have been translated into multiple Indian languages, and 15 million people around the globe learn on Khan Academy every month. Support Us: https://india.khanacademy.org/donate Created by Ashish Gupta