#Peaks handy calculator full

The undulating route, featuring the Newton Hills including the infamous Heartbreak Hill, requires strategic pacing in an effort to prevent a late-race bonk.Įnter The Pacing Project, “an advanced running pace calculator based on course specific terrain that can be used to create an optimal pacing strategy.” The Training Peaks-powered program allows one to select either goal time, recent race time or average pace on a similar course and adjusts your pacing chart for various races depending on the course’s elevation profile. The net downhill course notably drops approximately 450 feet (137m) over the course of 42.2K. The point-to-point race finishing in downtown Boston on Boylston Street begins in Hopkinton, Mass. In contrast, sequential testing methodologies are designed to allow for that “peeking” and decision-making mid-test, when the actual results cross the efficacy (better than expected) or futility (worse than expected) boundaries without reducing or invalidating those statistical controls.Chances are people running this year’s (or any other year’s) Boston Marathon know that the course is quite challenging relative to other big-city marathons. Ending a fixed horizon test early invalidates that control such that you cannot be sure what your actual false positive rate is. Say you want to use a 95% confidence level so that you’ve reduced your risk of a false positive to 5%.

#Peaks handy calculator full

For example, when the actual impact of your test is far greater than the MDE threshold, the fixed-horizon test method requires that you wait until you’ve achieved the full sample size before ending and making a decision on the test in order to not invalidate the statistical controls used to estimate sample size. The sequential test method reduces the penalty of having a bad prediction. Fixed-horizon tests that we’re all most familiar with use this threshold to determine sample size (run time). The MDE also represents a threshold of practical business impact. the Minimum Detectable Effect ), a baseline effect requirement for a successful test result. One required parameter for fixed-horizon tests is the Minimum Effect of Interest (a.k.a.

Namely, you’ll be able to make decisions more quickly when strong signals exist, and herein lies the primary benefit of sequential testing. However, if you can “peek” responsibly, you can gain some clear advantages. Making decisions to end a test early (because of peeking) compromises the statistical validity of your test.

We’ve all been tempted to “peek” for one reason or another, but most of the time this is hazardous. The sequential test calculator is designed to give you a structured way to manage your alpha (false positive) and beta (false negative) error rates to allow for responsible peeking. But you’ll want to start with this method rather than turning to it when the results show up as extreme (changing the rules of the game at halftime is just as inadvisable in statistics as it is in sports!). This R-based calculator provides a methodology for terminating fixed horizon tests early in the face of extreme results.īecause extreme results are hard to predict, and because when extreme results come around, you’ll want to act on them sooner, this tool provides you with the way to act on those results effectively. Sequential testing assesses data as it is collected, as opposed to assessing only once a full sample is collected, as in the case of fixed-horizon testing.

Analyze data while the test is running in order to determine if an early decision can be made.

What in the world is a sequential test calculator?ĭesigned and developed by our own Merritt Aho, the sequential test calculator provides experimenters with a responsible way to “peek “at test results and optimize test run times.