Prospectus

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Inferential Statistics for the Language Sciences

Course
2022-2023

Admission requirements

Successful completion of “Introduction to Methods and Statistics” is assumed. This course is only available for BA linguistics students.

Description

In this course students will get familiar with basic concepts in inferential statistics necessary to conduct research in (experimental) linguistics such as determining statistical power, bootstrapping, the chi-square test and other non-parametric tests, advanced correlation, linear regression, logistic regression, analysis of variance, and multilevel regression. For all techniques covered, the student will learn (1) the statistical theory behind the technique (2) how to practically perform the technique and (3) how to report the results. Furthermore, for all techniques covered, the student will learn how to set the sample size to obtain adequate statistical power and replicable results.

The focus of the course is on the correct application of statistical theory and the correct interpretation of statistical results in order to answer research questions in linguistics, not on mathematics.
Students will acquire practical data analysis skills through several assignments that are imbedded in experimental linguistics research. The student can choose to use SPSS or R statistical computing software

The course consists of obligatory lectures and workgroups.

Course objectives

Learning goal 1: student is able to describe core inferential statistics techniques in the language sciences

Learning goal 2: student is able to use SPSS or R software for core inferential statistics techniques in the language sciences

Timetable

The timetables are available through My Timetable.

Mode of instruction

Weekly lectures + workgroups

Assessment method

(1) Exam (learning goal 1); (2) Assignments (learning goal 1 and 2)
Student are allowed to miss a maximum of 1 workgroup. Handing in at least 9 out of 10 assignments of sufficient quality is obligatory in order to be eligible to participate in the exam.

Assessment

In order to pass: (1) Exam must be sufficient (55% correct) (2) 9/10 assignments need to be sufficient (submitted in time and of sufficient quality).
The final mark is based on the exam.

Resit

The exam can be retaken, the assignments cannot be retaken.

Inspection and feedback

How and when an exam review will take place will be disclosed together with the publication of the exam results at the latest. If a student requests a review within 30 days after publication of the exam results, an exam review will have to be organized.

Reading list

All students need (1) Leary and additionally need (2.1) Field for SPSS or (2.2.) Field for R.

  1. Leary, M.L. (2014). Introduction to Behavioral Research Methods (6th international edition). Pearson: Boston.
    2.1. Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th edition). Sage: London. OR
    2.2. Field, A. (2012). Discovering statistics using R. Sage: London

Registration

Enrolment through My Studymap is mandatory

Contact

For questions related to the content of the course, please contact the lecturer, you can find their contact information by clicking on their name in the sidebar.

For questions regarding enrollment please contact the Education Administration Office Reuvensplaats
E-mail address Education Administration Office Reuvensplaats: osz-oa-reuvensplaats@hum.leidenuniv.nl

For questions regarding your studyprogress contact the Coordinator of Studies

Remarks

not applicable