Confidence Regions and Pooling—Some Statistics for Weather Experimentation

The use of confidence intervals for assessing the results of weather modification experiments is demonstrated and is shown to be more informative than tests of significance. Multivariate tests, confidence regions, and simultaneous confidence intervals for multiple effects are discussed. Pooling of the results of several experiments is also described, both for single and for multiple effects. The methods are illustrated on ratio statistics applied to the first two Israeli experiments.