Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.
Statistics with Confidence is a widely acclaimed classic introduction to confidence intervals. The second edition, with contributions from leading medical statisticians, has been thoroughly revised and expanded.
Requiring little computational skills, the book offers user-friendly Excel spreadsheets for download at www.crcpress.com, enabling you to easily apply the methods to your own empirical data.
Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with the trade-offs between confidence and precision.
An example of the calibration problem where the models in Problem 10.7.5 is applicable is described in Smith and Corbett (1987), dealing with the accurate measurement of marathon running courses. The method of measurement is known as ...
This e-manual will make you an Excel Statistical Master of the confidence interval.
This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way.
Linear sequential rectifying inspection for controlling fraction defective, J. Roy. Statist. Soc. Suppl. 8, 216–222. Anscombe, F. J. (1952). Large sample theory of sequential estimation, Proc. Cambridge Philos. Soc. 48, 600–607.
Summarizes information scattered in the technical literature on a subject too new to be included in most textbooks, but which is of interest to statisticians, and those who use statistics in science and education, at an advanced ...
Inference and Linear Models. New York: McGraw Hill. Gauss, C.F. (1809). Theoria Motus Corporum Coelestium ... Analysis of Qualitative Data. Volume 1. Introductory Topics. ... Modelling Frequency and Count Data. Oxford: Clarendon Press.
Introduces many of the practical adaptive statistical methods and provides a comprehensive approach to tests of significance and confidence intervals.