Precision (statistics)

For broader coverage of this topic, see Accuracy and precision.

In statistics, the precision matrix or concentration matrix is the matrix inverse of the covariance matrix or dispersion matrix, .[1][2][3] For univariate distributions, the precision matrix degenerates into a scalar precision, defined as the reciprocal of the variance, .[4]

Other summary statistics of statistical dispersion also called precision (or imprecision[5][6]) include the reciprocal of the standard deviation, ;[3] the standard deviation itself and the relative standard deviation;[7] as well as the standard error[8] and the confidence interval (or its half-width, the margin of error).[9]

  1. ^ DeGroot, Morris H. (1969). Optimal Statistical Decisions. New York: McGraw-Hill. p. 56.
  2. ^ Davidson, Russell; MacKinnon, James G. (1993). Estimation and Inference in Econometrics. New York: Oxford University Press. p. 144. ISBN 0-19-506011-3.
  3. ^ a b Dodge, Y. (2003). The Oxford Dictionary of Statistical Terms. Oxford University Press. ISBN 0-19-920613-9.
  4. ^ Bolstad, W.M.; Curran, J.M. (2016). Introduction to Bayesian Statistics. Wiley. p. 221. ISBN 978-1-118-59315-8. Retrieved 2022-08-13.
  5. ^ Natrella, M.G. (2013). Experimental Statistics. Dover Books on Mathematics (in Italian). Dover Publications. p. 21-PA14. ISBN 978-0-486-15455-8. Retrieved 2022-08-14.
  6. ^ Balakrishnan, N. (2009). Methods and Applications of Statistics in the Life and Health Sciences. Methods and Applications of Statistics. Wiley. p. 537. ISBN 978-0-470-40509-3. Retrieved 2022-08-14.
  7. ^ Ellison, S.L.R.; Farrant, T.J.; Barwick, V. (2009). Practical Statistics for the Analytical Scientist: A Bench Guide. Valid Analytical Measurement. Royal Society of Chemistry. p. 145. ISBN 978-0-85404-131-2. Retrieved 2022-08-14.
  8. ^ Wilburn, A.J. (1984). Practical Statistical Sampling for Auditors. Statistics: A Series of Textbooks and Monographs. Taylor & Francis. p. 62. ISBN 978-0-8247-7124-9. Retrieved 2022-08-14.
  9. ^ Cumming, G. (2013). Understanding The New Statistics: Effect Sizes, Confidence Intervals, and Meta-Analysis. Multivariate Applications Series. Taylor & Francis. p. 366. ISBN 978-1-136-65918-8. Retrieved 2022-08-14.