Description
Book SynopsisChapter 1. Populations, Samples, Parameters, and Statistics.- Chapter 2. Some Probability Concepts.- Chapter 3. Estimation, Hypothesis Testing and the Scientific Method.- Chapter 4. Binary Random Variables and Acceptance Sampling Plans.- Chapter 5. Continuous Variables, the Normal Distribution, and the Central Limit Theorem.- Chapter 6. Continuous Variables and Acceptance Sampling Plans.- Chapter 7. Confidence.- Chapter 8. Some Confidence Interval Computations, Including Bootstrapping.- Chapter 9. Linear Regression, Correlation, and Least Squares.- Chapter 10. Analysis of Variance.- Chapter 11. Poisson and Exponential Variables, Rate, and Time-to-Event.- Chapter 12. 2k Factorial Experiments.- Chapter 13. Nonparametric Methods Rank-Based Tests, Permutation Tests and Resampling Methods.- Chapter 14. Nonlinear and Logistic Regression.- Chapter 15. Model Building.- Chapter 16. Multivariate Analysis.- Chapter 17. Bayesian Methods Markov Chain Montel Carlo Approach.- Chapter 18. Machine Learning and Data-Intensive Methods.- Chapter 19. Time Series and Dynamic Systems.- Index.
