Latest news
  • Old exams: Final August 2016 , Final January 2016 , Solutions August 2016 , Solutions January 2016
  • NB! Please be adviced that when I grade the projects I will search online and in URKUND to make sure you are handing in original work. That does not mean just the writing (URKUND) but that the analysis is a clear original piece of work (which I can check by searching for analysis of data sets with key terms). Trying to pass off work that is not your own constitutes cheating.... and consequences may be dire.
  • Mini 5: On Dec 16th you will present a short preliminary analysis of your project data. Prepare 4-6 slides and PRINT THEM. Bring to class and we will have a postersession where we go around and look at eachothers project and discuss. This is a great way to get feedback from me and your peers and perhaps get some inspiration.
  • Next week! Last week of class already! On Tue we will wrap up regularized regression. Thursday is a review lecture and Friday we go through old exams and the project presentations. I have booked the FB room on Friday for an extra 90 minutes for the presentations.
  • Old exams to be discussed on Friday: 2011 exam , Exam 2012 , Solutions 2012 , Solutions 2011 . Don't look at the solutions before you have given some thought to the exam questions!
  • NEW CLASSROOM: we will be in Euler on Tuesdays and FB on Fridays.
  • NEW CLASSROOM: Thursday 15/12 VASA A
    • Teachers
    Course coordinator: Rebecka Jornsten
    Office Hours: Thur 15-16.30 in MVH3029.
    Course litterature

    J.O. Rawlings, S.G. Pantula, D.A. Dickey. Applied Regression Analysis.
    Lecture notes
    You will use the statistical package R for the lab and project work.



    Programme
    Syllabus
    (pdf file)


    Preliminary Course Outline
    Week Chapter
    		 Topic
    45
    		 1:1-7,9, 11, 12:1-4
    		 Basics, Simple linear model, Diagnostics, Matrix formulation
    46
    		 2,3,4,(6), 11, 12, 13.1
    		 Multiple regression. Diagnostics and testing
    47
    		 9+notes
    		 ANOVA,ANCOVA, Model selection
    48
    		 7,13+notes
    		 Model selection
    49
    		 notes, 7
    		 Bootstrap, Cross-validation
    50
    		 13+notes
    		 Regularized regression
    51
    		 8,10,12,15
    		 WLS, NLM, GLM
    In-class presentations, Old Exams


    Lecture notes, Labs and MiniAnalyses
    Week Material
    		Labs and MiniAnalysis
    45
    		 Lecture 1 , Lecture 1 R code , The television data
    Demo , Demo1 , Demo 1b , The chocolate data

    Data sets for Demo - .RData objects: sleep.RData , house.RData


    Lecture 2 , Lecture 2 R code , Demo
    Lecture 3 , Lecture 3 R code

    		MiniAnalysis1
    Due Nov 8.


    46
    		Lecture 4 , Lecture 4 R code , Mini1 R code

    Lecture 5 , Lecture 5 R code , Demo 5 , pollution .RData file

    Lecture 6 , Lecture 6 R code , Demo 6


    		MiniAnalysis2 and Lab1
    Due Nov 18, RData with lab data


    47
    		 Lecture 7 , Lecture 7 R code , cars.dat, data set for demo 7.
    Lecture 8 , Lecture 8 R code , Demo 8 R code , SelAndPred.R , ModelSelection.R , CVcode.R
    Lecture 9 , Lecture 9 R code , Some Mini2 code , SA.dat South African Heart disease data     		MiniAnalysis 3 , due Nov 25
    48
    		 Lecture 10, Lecture 10 R code , cola.dat Cola data set
    Lecture 11, Lecture 11 R code , anorexia.dat Anorexia data set
    Mini 3 R code
    49
    		 Lecture 12, Lecture 12 R code
    Lecture 13 - CART , CART code , CART slides , wine data
    Lecture 14 - WLS and NLS , R code , More on NLS from An Appendix to An R Companion to Applied Regression, second edition , John Fox and Sanford Weisberg     		Mini4+Lab 2 - due Dec 9
    50
    		 Lecture 15, Lecture 15 R code , Bootstrap
    Lecture 16, Lecture 16 code
    Mini 4 code
    51
    		 Lecture 17, Lecture 17 code




    Assignments

    Labs and MiniAnalysis 10% (mandatory!), Project 30% and Final 60%
    Examination

    Written final + Final Project
    Old Exams

    I will post old exams here and we will spend the last week of classes going through them.
    Examination procedures
    In Chalmers Student Portal you can read about when exams are given and what rules apply on exams at Chalmers.
    At the link Scedule you can find when exams are given for courses at University of Gothenburg.
    At the exam, you should be able to show valid identification.
    Before the exam, it is important that you report that you want to take the examination. If you study at Chalmers, you will do this by the Chalmers Student Portal, and if you study at University of Gothenburg, so sign up via GU's Student Portal.

    You can see your results in Ladok by logging on to the Student portal.

    At the annual examination:
    When it is practical a separate review is arranged. The date of the review will be announced here on the course website. Anyone who can not participate in the review may thereafter retrieve and review their exam on Mathematical sciences study expedition, Monday through Friday, from 9:00 to 13:00. Check that you have the right grades and score. Any complaints about the marking must be submitted in writing at the office, where there is a form to fill out.

    At re-examination:
    Exams are reviewed and picked up at the Mathematical sciences study expedition, Monday through Friday, from 9:00 to 13:00. Any complaints about the marking must be submitted in writing at the office, where there is a form to fill out.