Statistical Analysis and Inference in Science: The Art of Reaching Conclusions at the Interface of Theory and Observation. Data and Data Management: What We Have to Go On or Accumulated Records of Observations and Their Expeditious Reorganization. Descriptive Statistics: First Impressions or Sketching Features of Observed Systems with Data. The Foundations of Inference: Probability Models as Descriptions of Research Outcomes. Stochastic Variables andthe Identification of Their Distributions: Distilling Uncertainty. The Exponential and Uniform Distributions: Describing Uncertainty in Time and Space. The Normal Distributions: Good Approximations for Many Composite Variables. AnalyzingVariability: Establishing Differences between Means and between Variances. Testing Hypotheses: Dealing with the Generic Critic while Establishing Powerful Support for New Ideas. Linear Regression: Analyzing an Influence Network. Bootstrapping: Scientific Inference when None of the Above Apply. Chapter Exercises. References. Subject Index.