Course Content

• Descriptive statistics; graphical displays for simple data sets; measures for the center and spread of data.
• Combinatorics; probability of various events using Venn diagrams, tree diagrams, and the addition and multiplication rules.
• Mutually exclusive events; conditional probability; dependent and independent events; and Bayes theorem.
• Random variables; probability distributions; expected value and variance.
• Discrete and Continuous probability distributions including Binomial, Negative-Binomial, Geometric, and Poisson distributions; and, normal (Gaussian), Exponential, F and T distributions.
• Sampling distribution and central limit theorem (CLT).
• Point and Interval estimation for population means and proportions (one and two samples).
• Hypothesis testing for population means and proportions; P-values in hypothesis testing.
• Correlation coefficient and Regression line equations; testing significance of linear relation; confidence interval and hypothesis testing for regression coefficients.
• Statistical inference tools for quality control.