Topic outline

  • General

    Please note that all the lectures and exercises of this course are given in zoom. Please note that neither the lectures nor the exercises are recorded, but the lecture slides are posted under "Materials"! Please note also that homework assignments are part of the grading.

    ZOOM LINKS TO THE EXERCISE SESSIONS:

    H03 (THU 8:15 - 10:00): https://aalto.zoom.us/j/68984767782


    H02 (THU 10:15 - 12:00): https://aalto.zoom.us/j/62368809410


    H04 (THU 12:15 - 14:00): https://aalto.zoom.us/j/67709062003

    H01 (THU 16:15 - 18:00): https://aalto.zoom.us/j/68173878509









    This course is an introduction to multivariate statistical analysis. The goal is to learn basics of common multivariate data analysis techniques and to use the methods in practice. Software R is used in the exercises of this course. The topics of the course are multivariate location and scatter, principal component analysis, bivariate correspondence analysis, multiple correspondence analysis, canonical correlation analysis, discriminant analysis, classification, and clustering.  

    Before the course starts, make sure that you know how to calculate the univariate means, medians, variances, and max and min values. Familiarize yourself with the correlation coefficients and common graphical presentations (boxplots, scatter plots, histograms, bar plots, pie charts) of data. Make sure that you know what is a cumulative distribution function, a probability density function, and a probability mass function. Make sure that you know what is the expected value of a random variable. Read about univariate and multivariate normal distributions and elliptical distributions. Make sure that you know what is meant by central symmetric distributions and skew distributions.

    How to pass this course?

    You are expected to:

    -Attend the zoom lectures and be active - not compulsory, no points, but highly recommended. Note that the lectures are not recorded! 

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

    -Take the exam - max 24 points. (The course examinations is on Thursday 15.4.)

    -Participate to weekly zoom exercises (group 1, group 2, group 3 OR group 4) - not compulsory, but highly recommended - max 3 points. Note that the zoom exercises are not recorded!

    -Be ready to present your homework solutions in the zoom exercise group - not compulsory, but highly recommended - max 3 points.

    Max total points = 6 + 24 + 3 + 3 = 36. You need at least 16 points in order to pass the course.

    How to get a good grade?

    -Attend the lectures and be active!

    -Work hard on your project work.

    -Be active in exercises!

    -Study for the exam!

    Grading is based on the total points as follows: 16p -> 1, 20p -> 2, 24p -> 3, 28p -> 4, 32p -> 5.