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7. Product and Process Comparisons
7.1. Introduction


What are trends in sequential process or product data?

Detecting trends by plotting the data points to see if a line with an obviously non-zero slope fits the points Detecting trends is equivalent to comparing the process values to what we would expect a series of numbers to look like if there were no trends. If we see a significant departure from a model where the next observation is equally likely to go up or down, then we would reject the hypothesis of "no trend".

A common way of investigating for trends is to fit a straight line to the data and observe the line's direction (or slope). If the line looks horizontal, then there is no evidence of a trend; otherwise there is. Formally, this is done by testing whether the slope of the line is significantly different from zero. The methodology for this is covered in Chapter 4.

Other trend tests A non-parametric approach for detecting significant trends known as the Reverse Arrangement Test is described in Chapter 8.
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