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# Smoothing data

In The resistant line section, we constructed our first regression model for the relationship between two variables. In some instances, the x-values are so systematic that their values are almost redundant, and yet we need to understand the behavior of the y-values with respect to them. Consider the case where the x-values are equally spaced; the shares price (y) at the end of day (x) is an example where the difference between two consecutive x-values is exactly one. Here, we are more interested in smoothing the data along the y-values, as one expects more variation in their direction. Time series data is a very good example of this type. In the time series data, we typically have xn + 1 = xn + 1, and hence we can precisely define ...

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