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PFG0069
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
PFG0069 Statistics III: Regression Analysis, 4.0 Credits
Subjects
Mathematical StatisticsEducation cycle
Postgraduate levelGrading scale
Pass / Failed
The requirements for attaining different grades are described in the course assessment criteria which are contained in a supplement to the course syllabus. Current information on assessment criteria shall be made available at the start of the course.
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
• interpret and evaluate results correctly and draw reasonable conclusions
• clearly and concisely communicate results and conclusion
Content
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.
Formats and requirements for examination
Passed exercises and passed examination in written and/or oral form.Responsible department
Department of Forest Resource Management