Tag: Statistics

  • Arduino Flickering Candle

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    Update December 24, 2013: Mokus refined his code so that the distribution is now well-behaved (nearly normal) and the PSD no longer turns up at high frequencies). The plots and post have been updated to reflect this change. He will push code to the same link as available. In my previous post on Candle Flame…

  • Ballistics and Repeatability – A Fuller Solution

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    The last post relied on the Monte Carlo method to determine the probability of correctly assessing relative accuracy. The linked document is a more a complete answer without any of the Monte Carlo drawbacks. 20091213_Hays-LoadComparisonStats

  • Ballistics and Repeatability

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    I have a rifle that shoots 3-inch 5-shot groups at 100 yards.  This is not adequate for hunting where commonly shots are 200 to 300 yards distant.  As I work toward resolving this, there are some interesting statistical problems of practical importance. In each experiment, how many shots should I fire to measure the spread,…

  • Coffee: Model Fitting Goodness

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    You have seen the response function contours through the stationary point, and you have seen the 3D response function visualizations. You may recall that I have two competing models, one is derived from the experimental data design for the response surface, and the other is all that data and the screening results too. Is either…

  • Coffee: Visualizing the Response Function

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    I have been calling my 3D response function a “surface”—which is linguistically feckless at best. Of course, I have some company, the immortal Box, Hunter, and Hunter call the experiment design a response surface method. So note carefully, the response function is not a surface, it completely fills a volume. Naturally, this is hard to…

  • Coffee: Analysis & Results of the Response Surface

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    I have executed the experiment design discussed Coffee: Design of the Experiments (Part 2: RSO). This “response surface method” experiment design is carefully crafted to provide the data necessary to fit a formula of the form q = b0T2 + b1t2 + b2r2 + b3Tt + b4tr + b5Tr + b6T + b7t + b8r…

  • Coffee: Design of the Experiments (Part 2: RSO)

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    In Review The results of my 4-trial fractional factorial experiment (main effects) showed that extraction time is the most important variable, and that temperature and C/W ratio are less important. In the interest of completeness this experiment will not simply vary extraction time, but rather seek to efficiently find the maximum. Lessons from the Screening…

  • Coffee: The Detestitron

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    Please, when you are shopping for a grinder, don’t believe anything you hear (except what I tell you…). A blade grinder is probably as good a grinder as you want to afford. Don’t presume that a burr grinder will automatically produce a more consistent grind. Take, for example, my manual burr machine. Compare the grind…

  • Coffee: Analysis & Results of the Main Effects Study

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    I have conducted the trials in the following table. Actual Values Statistics Jargon Trial r (g/ml) t (sec) T (F) r t T Q 1 0.035 10 205 -1 -1 +1 2.5 2 0.075 10 185 +1 -1 -1 3 3 0.035 300 185 -1 +1 -1 4 4 0.075 300 205 +1 +1 +1…

  • Coffee Design of Experiments (Part 1: Screening)

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    I will invoke a variety of principals from experiment design methods. The truth is, though, that I’m self-taught in experiment design. It is altogether probable that there are better ways of conducting this experiment which my ignorance has hidden from me. I’m open to suggestions! Quick Review The variables in control are temperature t, extraction…