The second half of a two part sequence covering various topics in probability and statistics. This course provides and introduction to essential techniques of statistical inference. Samples and statistics versus population and parameters. Distributions of functions and random variables. Sampling from the normal distribution. The t and F distributions. Point estimation by the method of moments and maximum likelihood estimation. Methods of evaluating point estimators. Finding and evaluating hypothesis tests and confidence intervals. Brief introduction to method of moments and maximum likelihood. Tests and intervals for means, variances and proportions (one and two sample). Regression models. Examples drawn from engineering, science, computer science, and business.