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I'm using a python function numpy.polyfit to describe lives sets of data in 10 second intervals as a 4th order polynomial.

I have considered normalising the data and adding a mask to the function to discover if it is trending as expected but would much prefer to use something like the slope of a linear line.

Is there a mathematical approach to discovering the trend of a high order polynomial function anyone could recommend?

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  • $\begingroup$ The trend is already in the data, the forth order polynomial is just a way of describing the data in the whole time interval (not just the data points). Can you show what the data looks like? It may be ok to get the trend just by linear regression in an adequate time interval. $\endgroup$ Commented Jul 10 at 9:58

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