Statistics for Physical Sciences and Engineering

At the end of this course students will be able to: 1. explain the measures of Central Tendency; 2. state the differences between Means, Median, and Mode; 3. explain the basic tenets of the Bayes Theorem and its uses; 4. distinguish between Discrete and Continuous Random Variables; 5. illustrate the differences between grouped and ungrouped dispersions in a graph; and 6. draw the tree diagram and explain its uses in statistics.

Measures of Central Tendency and Dispersion (Grouped and Ungrouped): Mean-Arithmetic, Geometric, Median, Mode, Qualities, Deciles and Percentiles. Empirical Relation between Means, Median, and Mode, their Relationship and absolute Dispersion. Simple Space and Events as Sets. Finite Probability Space; Properties of Probability Statistical Independence and Conditional Probability. Tree Diagram. Bayes Theorem. Discrete and Continuous Random Variables Expectation. Independent Bernoulli Trails. Binomial Passion and Normal Distributions. Normal Approximation to Binomial and Poisson Distributions. Hyper Geometric.