Semester: Sommersemester 2016

### 10.33.344 Introduction to statistics

Veranstaltungstermin

• Mittwoch: 08:00 - 10:00, wöchentlich

Beschreibung

The purpose of this course is to introduce students to the major concepts and tools for collecting, analyzing, and
drawing conclusions from data in the behavioural sciences, particularly psycholinguistics. Students learn to handle
data in SPSS, run relevant descriptive and inferential statistical analyses and interpret and report statistics in APA
style. Participants are exposed to a variety of conceptual themes and statistical tests, as listed below:

• Overview of methods of data collection in the social sciences and experimental linguistics, descriptive
versus inferential statistics
• Planning and conducting surveys and experiments, different types of data (nominal, interval, ordinal, ratio
data), Likert-scale, importing data from Excel or E-Prime into SPSS (pitfalls: commas, dots, etc.)
• Sampling and experimentation: Planning and conducting a study, designs (within- and betweenparticipant
• Exploring data: describing patterns and departures from patterns, splitting data, selecting cases
• Visualizing relationships in data, constructing and interpreting graphical displays of distributions of
univariate data (dotplot, stemplot, bar diagram, histogram, cumulative frequency plot)
• Traditional statistical inference, probability, one-tailed, two-tailed, Type I and II errors, misinterpretation
of the concept of probability, Bayes’ Law
• Mean, median, mode, range, StDev, SE, variance. Trimming data, handling RT data, mean or median, rules
and restrictions of trimming data, outliers (Z-transformation, SD criteria).
• The normal distribution (Shapiro-Wilk test, Kolmogorov-Smirnov test, Z-transformation and logtransformation
in psycholinguistic experiments), ANOVA assumptions
• Summarizing distributions of univariate data
• Parametric tests: independent/dependent samples t-test, ANOVA, ANCOVA, Linear regression, Multiple
linear regression, Levene’s test of homogeneity, post-hoc tests in ANOVA and corrections (LSD, Tukey,
Scheffe)
• Non-parametric tests: Friedman’s ANOVA, Kruskal-Wallis H, Mann-Whitney U, Wilcoxon signed ranks test,
Chi-square test, McNemar’s test, adjustments for multiple comparisons (Bonferroni, Holm-Bonferroni
sequential correction)
• Exploring bivariate data
• Exploring categorical data (binary Logistic Regression)
• Correlation: Spearman’s rho (nonparametric), Pearson (parametric), partial correlation; Fisher’s Z test (FZT
Computator)
• Different Effect-size measures (G-Power analysis, Cohen’s d, partial Eta squared: ηp
2; Prajapati et al., 2010)
• Measures of effect size (MES; Hentschke and Stüttgen, 2011; Prajapati et al., 2010)
• Multivariate data: Cluster analysis techniques and dendrograms (HCA, 2-step, K-means)
• item- and participant-based analyses, linear mixed-effects models
• generating the SPSS syntax file

References:
Hentschke H., Stüttgen M.C. (2011). Computation of measures of effect size for neuroscience data sets. European Journal of
Neuroscience, 34: 1887.
Prajapati, B., M. Dunne, Armstrong, R. (2010). Sample size estimation and statistical power analyses.
Optometry Today, 16.

DozentIn

TutorIn

Studienmodule

• ipb613 Sprachen
• lan010 Profilmodul
• lan021 Psycholinguistik I
• lan024 Psycholinguistik II
• lan027 Psycholinguistik III
• lan031 Sprachsystem und Variation I
• lan034 Sprachsystem und Variation II
• lan037 Sprachsystem und Variation III
• lan041 Sprachkontakt und Sprachwandel I
• lan044 Sprachkontakt und Sprachwandel II
• lan047 Sprachkontakt und Sprachwandel III
• mam Masterarbeitsmodul
• pb093 Erweiterte niederlandistische Sprach- und Kulturkompetenz
• pb094 Erweiterte niederlandistische Sprach- und Kulturkompetenz
• pb095 Erweiterte niederlandistische Sprach- und Kulturkompetenz
• pb096 Erweiterte niederlandistische Sprach- und Kulturkompetenz

Studienbereiche

• Anglistik
• Doktorandenkolloquien
• Language Sciences
• Niederlandistik
• Slavistik
• Weitere Veranstaltungen

Lehrsprache
englisch

empfohlenes Fachsemester
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