Lexical Scoping in R

Abstraction in OOP is the concept of hiding complex implementation details and showing only the essential features of the object. It focuses on what an object does instead of how it does it. This is achieved through abstract classes and interfaces, which define a blueprint for other classes without providing a complete implementation, simplifying complex systems.

The Finite Volume Method (FVM) is a dominant numerical technique in CFD for solving partial differential equations. It discretizes the domain into a mesh of control volumes and applies the governing equations in their integral form to each volume. By converting volume integrals to surface integrals using the divergence theorem, it focuses on calculating the flux of conserved properties across cell faces.

Formal verification is the use of mathematical methods to prove or disprove the correctness of a system's design with respect to a formal specification. Unlike testing, which can only show the presence of bugs for specific inputs, formal verification can prove their absence for all possible inputs. It involves creating a formal model of the system and using techniques like model checking or theorem proving.

Signal detection is the process of identifying potential causal relationships between a drug and an adverse event from large datasets, typically spontaneous reporting systems. It uses statistical methods, known as disproportionality analysis, to find drug-event combinations reported more frequently than expected. A common measure is the Reporting Odds Ratio (ROR), a value greater than one suggesting a potential signal that requires further investigation.

The Risk Priority Number (RPN) is a quantitative measure used in FMEA to prioritize risks. It is calculated as the product of three ranked factors: Severity (S), Occurrence (O), and Detection (D). The formula is \(RPN = S times O times D\). Each factor is typically rated on a scale from 1 to 10, allowing teams to focus on the highest-scoring risks first.

Verification and validation (V&V) are distinct processes. Verification ensures a product meets its specified requirements ("Are you building it right?"). Validation ensures the product meets the user's actual needs and intended use ("Are you building the right thing?"). They are complementary activities within quality management, often performed sequentially or in parallel to ensure both correctness and usefulness.

The repeatability limit, \(r\), is a critical value derived from the repeatability standard deviation (\(s_r\)). It represents the maximum expected absolute difference between two single test results, obtained under repeatability conditions, with a 95% probability. It is commonly calculated as \(r = 2.8 \times s_r\). If the difference exceeds \(r\), the results are considered suspect.