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@Lohring,All you have to do is take the scatter plots and connect lines of best fit and then you can see better your data variations and comparisons. Excel should have this ability. Also are you checking seeing which regression most accurately fits you data points? You should also be able to toggle between the data points and lines of best fit. Power, Logarithmic, Cubic, etc all have a linear regression, so there will be one that likely fits your data best. I did that as well as average the data from at least three runs. Some of my plots have these average lines on them. Our early tests had more scatter than our later tests, but the dyno's precision was about +- .1 hp. I measured the standard deviation between several identical runs at between 1 and 3%. Scatter plots keep people from making conclusions from the data that aren't justified.Lohring Miller

Jim has a very high accuracy water brake - see earlier in this thread.But some of the rest of us might find a cheaper / simpler measuring device interesting - more details please - though maybe in a separate thread.

Hi DRT, thanks for that explanation, it’s great to know a little of where you fit in.It is clear that some amazing work is being documented in this thread, and I normally just look on in awe (and silence). But I am interested in why, when you were talking about identifying those standing wave frequencies in excell, you went to regression analysis instead of the Fast Fourier Transform function. If it is a big enough data set, and that may of course be the problem, the FFT quickly identifies any natural frequencies in the data set.Oh, and also, please add my vote to Admiral DK for your build thread on a simpler dynamometer for us mere mortals.MJM460

the FFT quickly identifies any natural frequencies in the data set.