Bimodal Detector
Bimodal Detector
Extension stats
- activeTab
- declarativeContent
- tabs
Other platforms
Extension summary
Background
In a typical planning poker, i.e. for software development (to typically estimate the complexity of a ticket), estimates may differ between estimators. When do we need to discuss the different estimates, when don't we? One approach ist to detect multi-modality of the estimation distribution.
Example
A team estimates using typical scrum fibonacci numbers [0, 1, 2, 3, 5, 8, 13, 20, 40, 100]. And let's say, we have the following estimates after the first round: [1, 5, 5, 8, 3, 5]. Is this worth a discussion? I.e. is it uni- or multi-modal? The distribution (abundance) of the estimated fibonacci numbers looks like this: [0, 1, 0, 1, 3, 1, 0, 0, 0, 0]. This contains 2 local extrema which corresponds to a bi-modality. Discussion is worth between the two people having estimated a 1 and an 8, the lowest and the highest estimates.
Features
I distinguish two cases:
- Uni-modal distribution: I mark the median with a green background.
- Multi-modal distribution: I colorize the peaks of the distribution (those values which are most abundant) with a light red background color and extrema to discuss with a darker right background.
Extension safety
Risk impact
Bimodal Detector requires a few sensitive permissions. Exercise caution before installing.
Risk likelihood
Bimodal Detector may not be trust-worthy. Avoid installing if possible unless you really trust this publisher.
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