Bayesian statistical methodology and its possible uses in the behavioral sciences are discussed in relation to the solution of problems in both the use and teaching of fundamental statistical methods, including confidence intervals, significance tests, and sampling. The Bayesian model explains these statistical methods and offers a consistent model which ties together expectation of results, design of studies, analysis and predictions of future observations. A unique feature of the Bayesian approach is pre-posterior analysis in which one predicts what is likely to happen if a certain sample size is employed and then the expected gain of information is compared with the cost of taking the sample. Finally, this model forces a modeling of the decision making process employed in design and analysis. (PR)