Inhalt

[ 536DASCSTAV19 ] VL Statistics for AI

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B1 - Bachelor's programme 1. year Statistics Thomas Forstner 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2019W
Objectives Introduction into the research methodology in statistics and the basic principles of statistical thinking
Subject
  • Descriptive statistics: one and two dimensional characteristics
  • Correlation and linear regression
  • Basic concept of probability theorie including Bayes' theorem
  • Theory of random variables
  • Special distributions, test distributions
  • Estimating parameters: point estimation and interval estimation
  • Statistical hypothesis testing
Criteria for evaluation Examination
Methods Lecture by instructor
Language English
Study material
  • Slides provided by instructor
  • Bortz, J.: Statistik für Human- und Sozialwissenschaftler. Springer, Heidelberg
  • Fahrmeir, L.; Künstler, R.; Pigeot, I.: Statistik – Der Weg zur Datenanalyse. Springer, Berlin
  • Hartung, J.; Elpelt, B.; Klösener, K.-H.: Statistik: Lehr- und Handbuch der angewandten Statistik. Oldenbourg
  • or any other introductory book to statistics
Changing subject? No
Further information Continuative courses:

  • Statistics 2 (focus on parametric and non-parametric tests)
  • Special Topics: Computer Assisted Statistics with SPSS (introduction into SPSS)
  • Special Topics: Biostatistics in Clinical Research (introduction into biostatisics)
  • Special Topics: Applied Biostatistics
  • Special Topics: Statistics 3 (parametric and non-parametric analysis of variance, multiple linear and non-linear regression )
On-site course
Maximum number of participants -
Assignment procedure Direct assignment