Types of sampling, sampling distributions, estimators for population parameters, unbiasedness and mean square error of estimators, t and chi-square distributions, confidence intervals, hypothesis testing, two types of errors and their probabilities, sample size determination, linear and nonlinear least square regression equations for prediction. Computational techniques are used throughout the course.