# Statistical treatment of empirical data

Course Code : | 1030FBDBIC |

Study domain: | Biochemistry |

Academic year: | 2017-2018 |

Semester: | 1st semester |

Contact hours: | 20 |

Credits: | 4 |

Study load (hours): | 112 |

Contract restrictions: | No contract restriction |

Language of instruction: | Dutch |

Exam period: | exam in the 1st semester |

Lecturer(s) | Koen Janssens Karl Peeters |

### 1. Prerequisites *

- competences corresponding the final attainment level of secondary school

an active knowledge of

- Dutch

- English

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

specific prerequisites for this course

Knowledge of simple functions and graphs, derivatives of simple function.

The concept of integral of a functions. Basic operations with spreadsheets.

### 2. Learning outcomes *

- Report measured data in a correct way.
- Judge the quality of experimental data by their accuracy and precision.
- Compare experimental data with known values and with other experimental data.
- Construct a linear calibration curve, judge its quality and use it for prediction.
- Working with excel.

### 3. Course contents *

We first emphasis on the importance of experimental data as part of the scientific method and via a number of examples we illustrate the concepts systematic and random error. Next we develop in an intuitive manner the concept of probability density. We elaborate on the normal distribution, the central limit theorem and the propagation of errors.

With this basis we discuss the construction of confidence intervals for large datasets (z-statistic) and a small number of observations (t-statistics). In the chapter on statistical tests we show the use of the z- and t-statistic to compare experimental data under various conditions. We use the F-test to compare precisions of experimental data en the Q-test to remove outliers. In the last chapter the method of least squares fit of a straight line is introduced for the construction of calibration curves, its construction, evaluation and use.

For all of this, we use excel.

### 4 International dimension*

### 5. Teaching method and planned learning activities

Personal work

Directed self-study

**5.3 Facilities for working students ***

Others

Tutorials with theory, examples of exercises and excel skills on blackboard.

### 6. Assessment method and criteria

Permanent evaluation.

Examination

Continuous assessment

### 7. Study material *

#### 7.1 Required reading

Course notes available.

**7.2 Optional reading**

The following study material can be studied voluntarily :Tutorials about theory, examples of exercises and excel skills on blackboard.

### 8. Contact information *

Dr. Karl Peeters

Dept. of Chemisty

Campus Groenenborger

Groenenborgerlaan 171

Building V, room 109

email:karl.peeters@uantwerpen.be