← All parts of this equation

Equation 12 · Part 7 · Why Average Success Rate Hides the Failures That Matter Most

Probability operator

R=∑iPr⁡(failure mode i)⋅BiR = \sum_{i} \Pr(\text{failure mode } i) \cdot B_i
Pr⁡\Pr

What this part means

The probability operator gives the chance of the event named inside its brackets or parentheses.

Its job in the formula

Pr is one factor in the product that computes the quantity on the left.

The passage around this formula

Finding the failure is only half the design problem. The other half is scoring it, and a plain pass/fail count throws away exactly the information a consequence-aware evaluation needs — it treats a wrong word choice and a deleted database as the same unit. A more defensible score weights each discovered failure mode by its consequence rather than counting it once: R=∑iPr⁡(failure mode i)⋅BiR = \sum_{i} \Pr(\text{failure mode } i) \cdot B_i. where BiB_i is the blast radius assigned to failure mode i : how much of a system, how much data, how many users or how much liability a given failure could plausibly reach, drawn from a small number of severity tiers rather than treated as a continuous unknown. This is not a hypothetical scoring scheme; tiered,…

Read this part in the article →

Learn the underlying idea

Probability assigns a number from 0 to 1 to an event under a stated model. Zero means impossible within that model; one means certain.

Open the illustrated probability: a quantified chance guide →

Sources cited in the surrounding passage

These citations provide research context; check each source for the exact claim it supports.