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Confidence Interval Estimation for Means After Data Transformations to Normality.
- Source :
-
Journal of the American Statistical Association . Sep74, Vol. 69 Issue 347, p795. 8p. 2 Charts, 5 Graphs. - Publication Year :
- 1974
-
Abstract
- When data are transformed to satisfy a spherical normal linear model, the mean θ of a variate in the original scale is a function of the mean μ and variance σ² of a normal variate. We consider several approximate confidence interval methods for θ, including a new method based on exact confidence intervals for linear functions of μ and σ² Monte Carlo estimates of coverage probabilities demonstrate the suitability of the new method for applications involving a wide range of data transformations, parameter values and sample sizes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01621459
- Volume :
- 69
- Issue :
- 347
- Database :
- Academic Search Index
- Journal :
- Journal of the American Statistical Association
- Publication Type :
- Academic Journal
- Accession number :
- 4612407
- Full Text :
- https://doi.org/10.1080/01621459.1974.10480207