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PNS0180
Statistics III: Regression analysis
The course will cover the following topics:
• Simple linear regression.
• Multiple linear regression.
• Nonlinear models.
• Nonparametric regression and generalized additive models (GAM).
• Analysis of residuals.
• Simple linear regression.
• Multiple linear regression.
• Nonlinear models.
• Nonparametric regression and generalized additive models (GAM).
• Analysis of residuals.
Syllabus and other information
Syllabus
PNS0180 Statistics III: Regression analysis, 4.0 Credits
Subjects
Mathematical StatisticsEducation cycle
Postgraduate levelGrading scale
Pass / Failed
Prior knowledge
Statistics I: Basic Statistics or equivalentObjectives
The objective of the course is to give an overview of linear, nonlinear and nonparametric regression. On completion of the course, the student will be able to: • specify regression models including conditions and assumptions • select an appropriate regression model for a given problem • carry out a regression analysis in the statistical software R or SAS • interpret and evaluate results correctly and draw reasonable conclusions • clearly and concisely communicate results and conclusionsContent
The course will cover the following topics: • Simple linear regression. • Multiple linear regression. • Nonlinear models. • Nonparametric regression and generalized additive models (GAM). • Analysis of residuals.Responsible department
Department of Energy and Technology