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MS-E2112 - Multivariate Statistical Analysis D, 11.01.2021-15.04.2021

This course space end date is set to 15.04.2021 Search Courses: MS-E2112

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Syllabus
 

Assignments

  • Assignments

    Assignments

    Exercises

    Participate to weekly zoom exercises (group 1, group 2, group 3 OR group 4) - not compulsory, but highly recommended - max 3 points. If you attend 3-5 times, you get 1 point. If you attend 6-8 times, you get 2 points. If you attend at least 9 times (out of 11 times), you get 3 points.

    In order to earn the exercise points, you have to arrive on time to the zoom exercise session and write your name to chat as described below. You can not get any exercise points without attending the exercises.

    Exercise session 11 is reserved for the project work and for summarizing the contents of the course.

    Attending all the exercise sessions, including the last one, is highly recommended.

    Homework

    Solve the homework problems and be ready to present your solutions in the zoom exercise group - not compulsory, but highly recommended - max 3 points. Note that your solution does not have to be perfect or even correct --- trying your very best is enough!

    If you do your homework assignments  3-5 times, you get 1 point. If you do your homework assignments 6-8 times, you get 2 points. If you  do your homework assignments at least 9 times (out of 10 times), you get 3 points.

    In order to earn the homework points, you have to arrive on time to the zoom exercise session and type your name + attendance and homework to chat as described above. You can not get any homework points without attending the zoom exercises.

    Project Work

    Submit your project work on time - THIS IS COMPULSORY - max 6 points

    Find a multivariate (at least 3-variate) dataset (tilastokeskus, OECD, collect yourself, ...), set a research question, and perform multivariate analysis. Write a report (max 10 pages), and submit it below before Monday 12.4.2020 at 12.00!

    Goals of the project work:

    -Description of the research questions

    -Description of the dataset

    -Univariate and bivariate statistical analysis to present the variables

    -Application of your chosen multivariate statistical methods to answer research questions (justification and output)

    -Conclusions and answers to the question raised at the beginning

    -Critical evaluation of the analysis

    Remember that no findings is a finding!

    Note that you will automatically get 0 points from the exam if you will not submit your project work on time!

    About grading of the project work: 

    Maximum points are 6 and the 6 points are divided as follows.

    Intro (description of the research question and of the data source or data collection) --- max 0.5 p.

    Univariate analysis (description of the variables, summary statistics, visualization) --- max 1p.

    Bivariate analysis (analysis of bivariate dependencies, visualization) --- max 1 p.

    Multivariate analysis --- max 3 p. This is divided to selection of the method --- max 1 p.; technical implementation --- max 1 p.; and presenting the results/interpretation --- max 1 p.

    Critical evaluations (report about possible sources of biases etc.) --- max 0.5 p.

    If the report is not polished (blurry images, text in the marginal etc), that may lead to -1p.




    • icon for activity
      AssignmentProject work submission, deadline 12.4. at 12.00 Assignment
      • Exercise and homework 1Exercise and homework 1
        • Data1.txtData1.txt2.4KB
        • ex1.pdfex1.pdf124KB
        • ex1modified.htmlex1modified.html781.2KB
        • p1.pdfp1.pdf78.2KB
        • R1.RR1.R1.7KB
      • Exercise and homework 2Exercise and homework 2
        • DECATHLON.txtDECATHLON.txt3KB
        • ex2.pdfex2.pdf71.5KB
        • ex2mkd.htmlex2mkd.html988.1KB
        • p2.pdfp2.pdf72.6KB
        • R2new.RR2new.R3.5KB
      • Exercise and homework 3Exercise and homework 3
        • DECATHLON.txtDECATHLON.txt3KB
        • ex3.pdfex3.pdf81.1KB
        • ex3mkd.htmlex3mkd.html1017.7KB
        • p3.pdfp3.pdf72.5KB
      • Exercise and homework 4Exercise and homework 4
        • ex4.pdfex4.pdf90.9KB
        • ex4mkd.htmlex4mkd.html1.4MB
        • R4.RR4.R1.2KB
        • wood.txtwood.txt964 bytes
      • Exercise and homework 5Exercise and homework 5
        • ex5.pdfex5.pdf43.9KB
        • ex5mkd.htmlex5mkd.html787.3KB
        • p5.pdfp5.pdf85KB
        • R5.RR5.R2.5KB
        • SALARY.txtSALARY.txt126 bytes
        • SCIENCEDOCTORATES.txtSCIENCEDOCTORATES.txt761 bytes
        • SMOKING.txtSMOKING.txt143 bytes
      • Exercise and homework 6Exercise and homework 6
        • ca-package.pdfca-package.pdf239.1KB
        • ex6.pdfex6.pdf76.5KB
        • ex6mkd.htmlex6mkd.html1MB
        • p6.pdfp6.pdf73.5KB
        • R6.2.RR6.2.R5.1KB
        • SCIENCEDOCTORATES.txtSCIENCEDOCTORATES.txt761 bytes
        • SMOKING.txtSMOKING.txt143 bytes
      • Exercise and homework 7Exercise and homework 7
        • ex7.pdfex7.pdf69.4KB
        • ex7mkd.htmlex7mkd.html954KB
        • p7.pdfp7.pdf120.1KB
        • R7.RR7.R3.2KB
        • TEA.txtTEA.txt17.1KB
        • WG93_full.txtWG93_full.txt29.7KB
      • Exercise and homework 8Exercise and homework 8
        • CAR.txtCAR.txt1.1KB
        • DECATHLON.txtDECATHLON.txt3KB
        • ex8.pdfex8.pdf67.7KB
        • ex8mkd.htmlex8mkd.html848KB
        • R8.RR8.R4.5KB
      • Exercise and homework 9Exercise and homework 9
        • ALCOHOL.txtALCOHOL.txt3KB
        • ex9.pdfex9.pdf92KB
        • ex9mkd.htmlex9mkd.html766.3KB
        • p9.pdfp9.pdf81.7KB
        • R9.RR9.R2.5KB
      • Exercise and homework 10Exercise and homework 10
        • BANK.txtBANK.txt2.5KB
        • EMP.txtEMP.txt529 bytes
        • ex10.pdfex10.pdf60.6KB
        • ex10mkd.htmlex10mkd.html1.1MB
        • polls.txtpolls.txt516 bytes
        • R10_2.RR10_2.R3.8KB

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  • Schools
    • School of Arts, Design, and Architecture (ARTS)
    • School of Business (BIZ)
    • School of Chemical Engineering (CHEM)
    • –sGuides for students (CHEM)
    • – Instructions for report writing (CHEM)
    • School of Electrical Engineering (ELEC)
    • School of Engineering (ENG)
    • School of Science (SCI)
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    • Open University
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    • Aalto university pedagogical training program
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