Statistics training

Two-dayintensivestatistics courseI 2017

Current information on statistics training courses: see
www.uni-kassel.de/fb11agrar/de/fachgebiete-einrichtungen/umweltchemie/statistikschulungen.html

Statistical basics, experimental designs and introduction to R for soil scientists

The media and specialist journals from various disciplines repeatedly point to flawed research due to inadequate knowledge of statistics. For example, the Süddeutsche Zeitung wrote on February 5, 2016: "You might as well roll the dice - biomedical studies deliver questionable results". Ainsworth (2007, Nature 448, 849) puts it even more clearly: "The abysmal standard of statistical analysis in much of genetic epidemiology is little short of scandalous". There may also be similar problems in the soil sciences.

Typical problem areas in soil science could be, for example, (i) hypothesis-free research, (ii) inappropriate experimental designs, (iii) a lack of understanding of pseudoreplication, (iv) inappropriate handling of outliers, (v) lack of verification of conditions for hypothesis testing and (vi) inadequate description of statistical analyses in publications, so that the studies are not reproducible ("When necessary data were transformed", for example, is more of a text module than helpful information).

The intensive course will cover the statistical basics for soil scientists, including an introduction to R, so that the above-mentioned problem areas are less frequently encountered in soil science in the future.

Date: March 09, 2017 10:00 am to March 10, 2017 6:30 pm.

Location: University of Kassel, 37213 Witzenhausen, Nordbahnhofstr. 1a.

Costs: on request.

Number of participants: The number of participants is limited to 25.

Laptops: Please bring your own laptops with R and RStudio. If necessary, laptops can be borrowed with advance notice.

Materials: Course script, exercises and sample solutions will be provided.

Recommended literature: e.g. Crawley (2012). The R Book. 2nd Ed., Wiley.

Lecturer: Prof. Dr. Bernard Ludwig

Schedule of the intensive course:

Thu, 09.03.2017

10:00 - 12:00 Welcome, introduction to descriptive statistics and important distributions

12:00 - 13:00 Lunch break

13:00 - 14:00 Introduction to experimental designs, replication, pseudoreplication & hypothesis testing

14:00 - 16:30 Tests for normal distribution, variance homogeneity, parametric (various t-tests) and non-parametric tests (Wilcoxon rank sum tests), correlations according to Spearman and Pearson and chi-square tests

16:30 - 17:00 Coffee break

17:00 - 18:30 Introduction to R (data types)

Fri, 10.03.2017

10:00 - 12:00 Introduction to R (vectors & data frames, reading in data)

12:00 - 13:00 Lunch break

13:00 - 16:30 Exercises in R with practical examples: parametric and non-parametric tests

16:30 - 17:00 Coffee break

17:00 - 18:30 Exercises in R with practical examples: Correlations

Please send registrations and queries by 15.02.2017 to: Prof. Bernard Ludwig, University of Kassel, bludwig@uni-kassel.de

Please understand that the intensive course may be canceled if there are not enough registrations. In this case, or if the course is canceled due to illness of the lecturer or other events beyond our control, no further claims can be made.