Statistical methods for transportation data analysis

Learners completing this course should be able to: 1. utilize a comprehensive set of descriptive statistical methods, using common statistical software, in order to organize, summarize, and display data in a meaningful way; 2. use probability theory and common statistical software in order to evaluate the probability of real world events in transportation framework; 3. apply discrete and continuous probability distributions using common statistical software, in order to evaluate the probability of real world events in transportation framework; 4. construct confidence interval estimates for population parameters, using common statistical software, for single and multiple populations, based on sample data; 5. conduct hypotheses tests concerning population parameters, using common statistical software, for single and multiple populations, based on sample data; 6. perform multivariate analysis, using common statistical software, in order to estimate the nature and the strength of the relationship that may exist among a set of variables of interest; 7. perform supervised (regression and classification) analysis, using common statistical software, in order to: predict the value of one variable based on the values assumed by a set of predictors; and to estimate the magnitude of change in one variable due to a given change in other variables; and apply a comprehensive set of statistical tools using common statistical software, in making practical decisions and creating reports in workplace situations.