# Applied statistics

Course Code : | 1001WETTST |

Study domain: | Chemistry |

Academic year: | 2017-2018 |

Semester: | 1st semester |

Sequentiality: | Min. 8/20 for "Applied linear algebra I", "Applied calculus" and "Computer skills and statistical processing of measurements". |

Contact hours: | 25 |

Credits: | 3 |

Study load (hours): | 84 |

Contract restrictions: | No contract restriction |

Language of instruction: | Dutch |

Exam period: | exam in the 1st semester |

Lecturer(s) | Sandra Van Aert |

### 1. Prerequisites *

an active knowledge of

- Dutch

- general knowledge of the use of a PC and the Internet

specific prerequisites for this course

A basic knowledge of probability theory and elementary statistics acquired in the course "Computer skills and statistical processing of measurements" is assumed. More specifically, basic knowledge of programming in Matlab is assumed as well as basic knowledge of random variables, probability distributions and probability densities, estimation of population parameters, interval estimators and hypotheses testing. These topics will be briefly reviewed.

### 2. Learning outcomes *

- The student will be able to justify, explain and apply statistical methods with respect to concrete research questions.
- The student acquires an understanding of statistical methods.
- The student can make an appropriate choice between the different existing statistical methods.
- The student is able to construct an accurate reasoning (from analysis to solution and conclusion).
- The student can use the software Matlab.
- The student acquires a basic understanding of relevant scientific methods and techniques, develops in problem-solving skills, can synthesise and integrate different perceptions, and learns to apply and assess methods in a critical way.

### 3. Course contents *

The purpose of statistics is to summarize a large amount of data and from thisto retrieveuseful information.In the course "Applied statistics", the appropriate statistical methods to reach this goal are discussed and applied. The focus in this course is on practical exercises in which statistical methods are applied to a broad range of experimental data.

The course builds on the knowledge and skills acquired in the course "Computer skills and statistical processing of measurements" in BA1 . Knowledge and applications concerning random variables, probability distributions and probability densities, estimation of population parameters, interval estimators and hypotheses testing will be explored in greater detail. Next, the topic of statistical parameter estimation theory is discussed.

The course-content has the following chapters:

- General introduction : purpose of statistics
- Descriptive statistics : graphical and numerical representation to summarize the data
- Probability theory
- Univariate random variables : discrete and continuous random variables, probability distributions
- Multivariate random variables : joint probability distributions, covariance, correlation and variance
- Estimation of parameters : random sample averages, random sample proportions, random sample variance
- Interval estimation : setting up of reliability intervals
- Hypothesis testing : after a general introduction on testing, we deal with the most important tests for location, dispersion and distribution for different measurement scales and for 1, 2 or more than 2 populations respectively.
- Parameter estimation

### 4 International dimension*

### 5. Teaching method and planned learning activities

Personal work

Directed self-study

### 6. Assessment method and criteria

Continuous assessment

### 7. Study material *

#### 7.1 Required reading

Printed lecture notes available at the "cursusdienst". Additional examples, slides, exercises are provided via Blackboard.

**7.2 Optional reading**

The following study material can be studied voluntarily :There is no additional literature that the students should read.

### 8. Contact information *

Sandra.VanAert@uantwerpen.be

Annick.DeBacker@uantwerpen.be