376-1719-00L  Statistics for Experimental Research

SemesterSpring Semester 2019
LecturersR. van de Langenberg
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
376-1719-00 VStatistics for Experimental Research2 hrs
Tue10:15-12:00HG D 1.1 »
R. van de Langenberg

Catalogue data

AbstractStudents will learn the necessary statistical concepts and skills to independently (1) design experiments (2) analyse experimental data and (3) report analyses and results in a scientifically appropriate manner.
ObjectiveAfter successful completion of the course, students should be able to:
1. Determine appropriate experimental designs and choose, justify and perform the appropriate statistical analyses using R.
2. Report analyses and results in a scientifically appropriate manner, as laid out by the Publication Manual of the American Psychological Association (APA, sixth edition).
ContentWe will cover basic statistical concepts (e.g., central tendency, variability, data distribution), the t-test (dependent and independent), ANOVA (univariate, factorial and repeated measures), correlation, multiple regression, nonparametric techniques, validity and reliability tests, effect size, data transformation, power and sample size estimation.
Lecture notesLecture notes will be delivered in the form of commented presentations in Microsoft Powerpoint (i.e. pptx) format. R practical session assignments will be delivered in pdf-format.
LiteratureBoth in the lectures and in the tutorials and practical sessions, we will refer students to the following publication:

Field A, Miles J, Field Z (2013) Discovering Statistics Using R. Sage Publications Ltd, London, UK

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersR. van de Langenberg
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

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Restrictions

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Offered in

ProgrammeSectionType
Doctoral Department of Mechanical and Process EngineeringDoctoral and Post-Doctoral CoursesWInformation
Health Sciences and Technology MasterElectives Courses IWInformation