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Read engineering data with more confidence. Explore sampling, distributions, causal inference, and experiments that distinguish a real improvement from ordinary variation.

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127 terms
  • Reliability

    Reliability is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Reproducibility

    Reproducibility is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Research hypothesis

    Research hypothesis is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Sample size

    Sample size is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Seasonality

    Seasonality is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Sensitivity analysis

    Sensitivity analysis is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Service template

    A service template is a reusable starting point for creating a software service and its supporting configuration. It may include repository structure, build and deployment workflows, observability, security controls, documentation, and defaults that teams can adapt to their context.

    Measurement and experimentation
  • Simpson's paradox

    Simpson's paradox is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Skewness

    Skewness is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Software factory improvement experiment

    A software factory improvement experiment is a time-bounded change to a software delivery system that tests whether a specific intervention improves a defined outcome. It uses a baseline, a stated hypothesis, comparable measures, and a review of the evidence before the change is adopted more broadly.

    Measurement and experimentation
  • Software factory metrics

    Software factory metrics are a defined set of measurements used to understand how an organization's software delivery system performs. They cover the movement, quality, stability, cost, and experience of work rather than reducing the factory to one activity count.

    Measurement and experimentation
  • Special cause variation

    Special cause variation is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Standard error

    Standard error is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Stationarity

    Stationarity is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Statistical process control

    Statistical process control is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • SUTVA

    SUTVA is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • T-test

    T-test is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Treatment effect

    Treatment effect is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Treatment group

    Treatment group is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Treatment spillover

    Treatment spillover is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Type i error

    Type i error is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Type ii error

    Type ii error is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Unit of analysis

    Unit of analysis is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Validity

    Validity is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Welch's t-test

    Welch's t-test is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Wilcoxon signed-rank test

    Wilcoxon signed-rank test is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation
  • Z score

    Z score is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.

    Measurement and experimentation