SEE2003 - Introduction to Energy and Environmental Data Analysis | ||||||||||
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| * The offering term is subject to change without prior notice | ||||||||||
Course Aims | ||||||||||
The course will provide students with the knowledge of using statistical methods in energy and environmental science.? Analysis methods, such as probability, random variable (discrete & continuous), parameter estimation, confidence internal and hypothesis testing, inferences involving one and two populations, simple linear regression, analysis of variance and goodness-of-fit test, are very helpful for students to understand the physical processes occurring in the environment, and to work on climate prediction.? Students are required to use the knowledge learnt from this course to analyse the data with computational tools, such as Python.? Overall, students would gain the understanding of statistical methods in energy and environmental science and they would be capable to analyse the data using statistical methods. | ||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||
Continuous Assessment: 65% | ||||||||||
Examination: 35% | ||||||||||
Examination Duration: 2 hours | ||||||||||
To pass a course, a student must do ALL of the following: 1) obtain at least 30% of the total marks allocated towards continuous assessment (combination of assignments, pop quizzes, term paper, lab reports and/ or quiz, if applicable); 2) obtain at least 30% of the total marks allocated towards final examination (if applicable); and 3) meet the criteria listed in the section on Assessment Rubrics. | ||||||||||
Detailed Course Information | ||||||||||
| SEE2003.pdf | ||||||||||
