Least squares trend analysis involves fitting a straight line through a series of data, which, by definition:

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Least squares trend analysis aims to minimize the sum of the squared residuals (the vertical distance between each data point and the trendline) by finding the line that best fits the data. This means that the distance of each data point from the line is minimized, and the squared area above and below the trendline is also minimized. The number of data points required for a usable trendline may vary based on the specific situation, but there is no set minimum of 20 points. The trendline does not need to include a peak or a trough, as it is simply a line that represents the overall trend in the data.

Least Squares Trend Analysis Involves Fitting a Straight Line Through