Statistics for Masters Students at LMU faculty of biology, Summer Semester 2021

Prof. Dr. Dirk Metzler


Schedule for the next sessions for questions and exercises

Videos

Videos on the statistics software R

part 1 (duration [min:sec]: 21:08), part 2 (19:04), part 3 (20:27), part 4 (20:12), part 5 (22:17), part 6 (13:34), part 7 (12:25)

Lecture videos

The videos contain some material from last year but may be updated during the semester or even some topics may be replaced.
  1. Descriptive Statistics: part 1 (duration [min:sec] 53:03), part 2 (36:55)
  2. Standard Error of the Mean: video (39:11)
  3. Basic concepts from probabilty theory:
    part 1: Probabilities and random variables (87:40),
    part 2: Expectation values, variances, covariances and correlations (81:23)
    part 3: Applications in quantitative genetics: Robertson-Price formula and the breeder's equation (53:59)
    part 4: Probability densities, normal approximations and the z-Test (50:00)
  4. t-Tests and the general principles of statistical testing (and non-parametric alternatives to the t-test):
    one-sample t-tests; checking model assumptions, e.g. with qqnorm plots (39:03)
    optional: biological application examples for t-tests (82:43)
    optional: Wilcoxon' signed rank test (15:48)
    The principle of statistical testing (24:32)
    Two-sample t-tests; important aspect of testing: avoiding dependence in the data (45:32)
    optional: Wilcoxon' rank sum test (Mann-Whitney U test) (15:52)
  5. Analyses of variance (ANOVAs) and on multiple-testing corrections (127:39)
    optional: Kruskal-Wallis test (9:09)
  6. Chi-square tests and Fisher's exact test: video (65:59)
  7. Linear Models: part 1 (69:54), part 2 (81:51)
  8. Linear Mixed-Effects Models: video (98:12)
  9. Generalized Linear Models (GLMs): video (136:16)

Handouts

Material will be added during the course. Please note that the handouts will not form a complete script. They only summarize the contents of the slides shown during the lecture. You will need to complement the handouts with your own notes during the lecture and read text books.
  1. Descriptive Statistics, bluearea.csv
  2. Standard Error
  3. Basics from Stochastics
  4. t-Tests and Wilcoxon's signed rank test, more biological t-test examples, Wilcoxon test application aspects (with biological examples)
  5. Comparing more than two groups: multiple testing issues, ANOVA and Kruskal-Wallis
  6. Chi-square and Fisher's exact test
  7. Linear Regression
  8. Linear Mixed-Effects Models
  9. Generalized Linear Models

Exercises

Solving these exercise problems is an effective way to improve your understanding of the lecture contents. We will discuss your solution during the exercise sessions in the moodle forum or via online video meeting. If you like, you can send your solutions to the course instructor by uploading them on the moodle page of the course. If you do this early enough (two days before the session to be on the safe side), you may get feedback on your solution from the instructor before the exercise session. Before a particular exercise is discussed in an exercise session, you can already ask questions on the exercises in the moodle forum and give each other some hints, but please make sure that you do not tell too much at this point, so that all others have the chance to find their own solutions.
sheet0.pdf
sheet1.pdf, swarth1.txt
sheet2.pdf
sheet3.pdf, sem_cll.R
sheet4.pdf
sheet5.pdf, yield.csv
sheet6.pdf, gene_p_values.csv
sheet7.pdf, songtime.csv, catfish.txt
sheet8.pdf moreqqplots.pdf
sheet9.pdf, chilis.csv, RNASeq_K_Na.csv
sheet10.pdf
sheet11.pdf

Quantile Tables

The R statistics software

Examples of R commands: R_intro.R, FinchesSulloway.txt, swarth1.txt
There are several graphical user interfaces for, as for example RStudio.

Literature

Last Change: Dirk Metzler, 20. April 2022