Module: Applied Statistics (1102-210)

This module not offered anymore!

Persons:

• apl ProfDr Uwe Jensen (verantwortlich)

Degree Program:

• Food Science and Biotechnology (Bachelor, since 01.04.2011)
  5. Semester, elective
• Nutritional Management and Dietetics (Bachelor, since 01.04.2011)
  5. Semester, elective
• Agricultural Biology (Bachelor, since 01.10.2015)
  5. Semester, elective
• Nutritional Management and Dietetics (begin of studies WS 2017/18) (Bachelor, since 01.10.2017)
  5. Semester, elective
• Biologie Lehramt an Gymnasien (Master, since 01.10.2017)
  1. Semester, elective
• Biologie Lehramt an Gymnasien (Master, since 01.10.2017)
  3. Semester, elective
• Biologie Lehramt an Gymnasien | Erweiterungsmaster (Master, since 01.10.2017)
  3. Semester, elective
• Agricultural Biology (from WS 17/18 on) (Bachelor, since 01.10.2017)
  5. Semester, elective
• Agricultural Biology (from WS 18/19 on) (Bachelor, since 01.04.2018)
  5. Semester, elective
• Biology (Bachelor, since 01.04.2011)
  5. Semester, semi-elective
• Biology (Bachelor, since 01.04.2011)
  5. Semester, semi-elective
• Nutritional Science (Bachelor, since 01.04.2011)
  5. Semester, elective

Relation to other Modules:

This module forms together with the modules "Analytical Biochemistry" and "Instrumental Analysis" or "Biologically Active Compounds" the elective profile Bioanalytics for the study programme "Biology"

Prerequisites for Attendance:

Knowledge equivalent to the module "Mathematics for Life Sciences"

Sprache:

German

ECTS:

6 credits

Frequency:

every winter semester

Length of the Module:

1 semester

Compulsory assignment:

Regular and active participation, solving exercises during the practical course

Module examination:

Written exam

Length of the examination:

120 minutes

Workload:

72 h presence + 98 h personal contribution = 170 h workload

Professional competences:

Contents:

1. Probability Theory
Probability, random variable, distribution, independence, expectation, variance, correlation, central limit theorem

2. Inferential Statistics
Confidence intervals, hypothesis testing in models with normal distribution, nonparametric models, analysis of variance (ANOVA), linear regression

3. Statistics with SAS
Introduction to the software package, descriptive statistics, graphical representation of data sets, classical parametric and nonparametric hypothesis testing, linear models, analysis of real data sets with interpretation of results

Comments:

Maximum number of participants: 35

eLearning:

Course in ILIAS

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