• Observational error (or measurement error) is the difference between a measured value of a quantity and its unknown true value. Such errors are inherent...
    16 KB (2,134 words) - 22:17, 17 December 2023
  • sample from its "true value" (not necessarily observable). The error of an observation is the deviation of the observed value from the true value of a...
    16 KB (2,168 words) - 18:00, 25 November 2023
  • Thumbnail for Margin of error
    the measure varies. The term margin of error is often used in non-survey contexts to indicate observational error in reporting measured quantities. Consider...
    13 KB (2,192 words) - 19:08, 5 January 2024
  • Thumbnail for Observation
    presence Naturalistic observation Observation unit Observational astronomy Observational error Observational learning Observational study Observable quantity...
    14 KB (1,599 words) - 20:44, 4 April 2024
  • Accuracy and precision are two measures of observational error. Accuracy is how close a given set of measurements (observations or readings) are to their...
    23 KB (2,843 words) - 16:42, 25 April 2024
  • Thumbnail for Statistics
    conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). Descriptive statistics are most often concerned...
    78 KB (8,784 words) - 23:50, 27 May 2024
  • common error). Independence of observational error from potential confounding effects. Exact or approximate normality of observations (or errors). Linearity...
    6 KB (703 words) - 05:54, 29 April 2024
  • Thumbnail for Least squares
    considers only observational errors in the dependent variable (but the alternative total least squares regression can account for errors in both variables)...
    38 KB (5,493 words) - 12:12, 31 May 2024
  • Thumbnail for Artifact (error)
    In natural science and signal processing, an artifact or artefact is any error in the perception or representation of any information introduced by the...
    6 KB (676 words) - 13:19, 6 May 2024
  • In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. For example...
    31 KB (4,487 words) - 23:50, 2 May 2024