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  "body": "\n## Summary\n\nLinear regression models a response variable as a linear function of explanatory variables plus a random error.\nThe model is linear in the unknown coefficients, not necessarily in the explanatory variables themselves.\nIts coefficients are most often estimated by [[ordinary least squares|YM708KHV2W]].\nIt is one of the most widely used statistical models, and the base of the [[general linear model|A06SGFCSCE]] and its extensions.\n\n## Explanations\n\n### L1 human\n\nPlot the heights of children against their ages, and the points lie roughly along a line.\nLinear regression describes the height as an intercept plus a slope times the age, plus a random deviation for each child.\nThe slope says how much height increases per year on average.\nWith several explanatory variables, such as age and parents' heights, the line becomes a plane or a higher-dimensional flat surface.\n",
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