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Which of the following assumptions is a robustness factor suitable for validating statistical conclusions?
Robustness in statistical conclusions often refers to the ability to draw valid conclusions even when certain assumptions are violated. One of the critical factors for robustness is high statistical power, which refers to the probability of correctly rejecting the null hypothesis when it is false. Reason: High statistical power increases the likelihood that the test will detect a true effect if it exists, thereby supporting the validity of the conclusions.
Risk control includes making decisions using which of the following pieces of information?
Risk control involves making decisions using information about acceptable levels of risk. This process helps ensure that the risks associated with various activities are managed within tolerable limits, balancing the potential impact with the organization's risk appetite.
'Risk Management: Concepts and Guidance' by Carl L. Pritchard
ISO 31000: Risk Management guidelines
Choosing design settings to minimize the effect of noise is a goal of
Robust design focuses on improving the quality of a product by minimizing the effects of variations without eliminating the causes of those variations.
Robust Design:
Techniques to make products or processes less sensitive to variations.
Aim to ensure performance under a wide range of conditions.
Tolerance Design:
Setting acceptable ranges of variation for product dimensions or performance metrics.
Design Verification:
Testing and validating that a design meets its requirements.
Design for Maintainability:
Designing products to be easy to maintain and repair.
Choosing design settings to minimize the effect of noise aligns with robust design principles.
Which of the following statements BEST describes a bimodal distribution?
Which of the following definitions describes severity?
Severity in the context of software quality and risk management refers to the extent of impact a failure would have on a system or process.
It assesses the consequences of a failure, regardless of its likelihood or detectability.
High severity indicates significant detrimental effects, such as critical system failures or safety hazards.
Reference: The ASQ and FMEA (Failure Mode and Effects Analysis) methodology define severity as the measure of the seriousness of the effect of a failure mode.
