Course Code : | 1001WETEST |

Study domain: | Mathematics |

Academic year: | 2019-2020 |

Semester: | 2nd semester |

Sequentiality: | Minimum 8/20 for Calculus. |

Contact hours: | 30 |

Credits: | 3 |

Study load (hours): | 84 |

Contract restrictions: | No contract restriction |

Language of instruction: | Dutch |

Exam period: | exam in the 2nd semester |

Lecturer(s) | Tim Verdonck ValĂ©rie De Witte |

At the start of this course the student should have acquired the following competences:

an active knowledge of

an active knowledge of

- Dutch

Basic knowledge of mathematics

- you understand the basic concepts of probability theory and know how to apply this theory to solve new probability problems;
- you can analyze a sample with descriptive statistics and interpret the results correctly;
- you learn to deal with data from diverse research domains in a scientific way;
- you understand the general framework of parameter estimation, confidence intervals, hypothesis testing and linear regression and know how to apply this theory in some specific cases (e.g. t-tests for normal variables), in written exercises as well as using statistical software;
- you know the mathematical basis of statistics, learn to think formally and are able to work with the software R.
- given a data set and some specific research questions, you are able to translate the problem on your own and in a creative way into a statistical model and to formulate a correct answer by means of appropriate statistical techniques.
- You can present your results in a written report.

- The basics of probability theory are explained. The mathematical definition of a probability distribution is given and several probability rules are derived. The student is able to apply the theory in concrete probability problems.
- Some specific discrete and continuous probability distributions are discussed (binomial, normal etc.).
- The basic theory of descriptive statistics, parameter estimation, confidence intervals and hypothesis tests is explained. Specific cases (e.g. t-test for normal distributions) are treated in more detail. The statistical software program R is used to apply this theory.
- Finally a short introduction is given to linear regression. The main focus is on the correct use and interpretation of the output of the software program R.

Class contact teachingLectures Practice sessions Laboratory sessions

Personal workExercises

Personal work

Written assignment

Examination

Written assignment

Course notes and slides are available through blackboard.

Books:

- Montgomery, D.C. and Runger G.C. Applied Statistics and Probability for Engineers.
- Agresti, A. and Franklin, C. Statistics - The Art and Science of Learning from Data.

Professor: Tim Verdonck (Tim.Verdonck@uantwerpen.be)