The course commences with the basic concepts of Statistics including population versus sample, descriptive and inferential statistics and data types. Methods of visualizing patterns of variation using pictures or graphs, such as stem-and-leaf displays, run charts, pie charts, bar graphs, and histograms are studied. When graphical representations do not lend themselves to inference making, numerical descriptive measures must be used to indicate location, shape, and spread in a data set. Numerical analysis is accomplished using mean, medium, midrange, range, percentiles, variance, Interquartile Range (IQR), and standard deviation. Basic probability concepts are introduced since analysis, in Statistics, is based on probability. Discrete probability distributions that play an important role in technical applications include the Hypergeometric, Binomial, and Poisson. Continuous distributions are handled using the Normal distribution (bell curve). Finally, to help make statistical inferences about populations, sampling distributions and interval estimates are studied.