752-2110-00L  Multivariate Statistical Analysis

SemesterSpring Semester 2021
LecturersC. Hartmann, A. Bearth
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
752-2110-00 VMultivariate Statistical Analysis Special students and auditors need a special permission from the lecturers.
Permission from lecturers required for all students.
2 hrs
Thu10:15-12:00HG D 12 »
10:15-12:00HG D 7.2 »
10:15-12:00HG E 19 »
C. Hartmann, A. Bearth

Catalogue data

AbstractThe course starts by introducing some basic statistical concepts and methods, e.g. data exploration, the idea behind significance testing, and the use of the statistical software SPSS. Based on these fundaments, the following analyses are discussed: regression analysis, factor analysis and variance analysis.
ObjectiveStudents will learn to use multivariate analysis methods and to interpret their results, by means of theory and practice.
ContentThis course provides an introduction into the theories and practice of multivariate analysis methods that are used in the fields of food sensory science, consumer behavior and environmental sciences. The course starts by introducing some basic statistical concepts and methods, e.g. data exploration, the idea behind significance testing, and the use of the statistical software SPSS. Based on these fundaments, the following analyses are discussed: regression analysis, factor analysis and variance analysis. During the course, theoretical lectures alternate with practical sessions in which data are analyzed and their results are interpreted using SPSS.


Agenda (for further information see Moodle course)

25.02 Introduction to the course and basic concepts of multivariate statistics

04.03. Data handling and exploration + SPSS Introduction

11.03. Exercise 1a+b

18.03. Basic Statistical Tests

25.03. Exercise 2: Basic Statistical Tests

01.04. Regression analysis

15.04. Exercise 3: Regression analysis

22.04. Variance Analysis

29.04. Exercise 4: Variance Analysis

06.05. Reliability Analysis

20.05. Principle Component Analysis

27.05. Exercise 5: PCA and Reliability Analysis

03.06. EXAM (Room will be announced)
LiteratureField, A. (2013). Discovering Statistics Using SPSS (4th edition). Sage Publications. ISBN: 1-4462-4918-2 (and any other edition)
Prerequisites / NoticeThis course will be given in English.
The course will take place online via zoom.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersC. Hartmann, A. Bearth
Typeend-of-semester examination
Language of examinationEnglish
RepetitionA repetition date will be offered in the first two weeks of the semester immediately consecutive.

Learning materials

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

Groups

No information on groups available.

Restrictions

General : Special students and auditors need a special permission from the lecturers
Permission from lecturers required for all students

Offered in

ProgrammeSectionType
Food Science MasterMethodology SubjectsWInformation
Food Science MasterMethodology SubjectsWInformation
Food Science MasterMethodology SubjectsWInformation
Food Science MasterMethodology SubjectsWInformation
Food Science MasterFood Sensory Science and Consumer BehaviourWInformation
Environmental Sciences MasterModeling and Statistical AnalysisWInformation