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This lesson focuses on the importance of standardizing data in order to make comparison easier. Many real-world datasets have variables measured on different scales, which can lead to misinterpretation. Standardizing data involves centering the distribution around the mean and calculating the number of standard deviations each point is away from the mean. This can be done by calculating z-scores, which help in putting all variables on the same scale. Standardization helps in accurately comparing variables and avoiding misinterpretation of the data.
