Data are fundamental to transport decision making. This unit applies rigorous probabilistic and statistical techniques to the analysis of data commonly encountered in transport studies. You will develop an understanding of probabilistic and statistical analysis procedures and their application to analysis of univariate and multivariate data, the model development process and its application to range of modelling techniques employed in the analysis of transport data.
The minimum total expected workload to achieve the learning outcomes for this unit is 150 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.
Estimate and appraise suitable probabilistic models for transport and traffic problems,
Estimate and evaluate the robustness of statistical models for understanding current, or predicting/forecasting future, travel/traffic conditions.
Infer the characteristics of a population based on a sample of that population drawing on appropriate statistical techniques, and
Justify the relevance of quantitative data analysis skills for contemporary transport and traffic practice,
You will conduct a preliminary analysis of a real-world multivariate data set.
The final assessment will consist of a number of short case-study problems that require statistical analysis
You will complete a series of mini-tasks concerning the multivariate data set (introduced in Assignment 1) that will test your abilities to correctly apply and interpret some of the more advanced statistical procedures learnt in the unit.
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