Study Programmes 2015-2016
| MATH1472-1 | |||||
Probability and Statistics I
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Duration :
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| Part 1 : Descriptive Statistics : 16h Th, 8h Pr, 8h Mon. WS Introduction to probability : 9h Th, 7h Pr, 2h Mon. WS |
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Number of credits :
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Lecturer :
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| Part 1 : Descriptive Statistics : Gentiane Haesbroeck
Introduction to probability : Gentiane Haesbroeck |
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Coordinator :
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| Gentiane Haesbroeck | |||||
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Language(s) of instruction :
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| French language | |||||
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Organisation and examination :
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| Teaching in the second semester | |||||
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Units courses prerequisite and corequisite :
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| Prerequisite or corequisite units are presented within each program | |||||
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Course contents :
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| Look at the contents of the two parts. | |||||
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Part 1 : Descriptive Statistics
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| Basic concepts of descriptive statistics are taught in this course. More precisely, here follows the content of the course:
- Statistical tables and graphics - Summary statistics (central tendency, dispersion and shape) - Correlation analysis and linear regression The learning of a statistical software is also included in the material of the course. |
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Introduction to probability
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| This partim 2 is dedicated to a complement of descriptive statistics (M-estimation, geometric, harmonic and generalized means, Lorenz curve and Gini index) and to an introduction to probability theory. | |||||
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Learning outcomes of the course :
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| Look at the learning outcomes of the two partims. | |||||
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Part 1 : Descriptive Statistics
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| After this course, the student should be able to present data appropriately, compute appropriate parameters in order to analyse data and interpret the results. | |||||
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Introduction to probability
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| After this part, the student should be able to formalize the estimation process for the centre of a distribution, to adpat the definition of the mean to the context and to model the distribution of the wages of a population in order to compute a measure of inequality.
Additionaly, the student should be able to use correctly probability calculus. |
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Prerequisite knowledge and skills :
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| look at the prerequisites for each part. | |||||
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Part 1 : Descriptive Statistics
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| basic concepts of analysis and algebra taught in secondary school. | |||||
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Introduction to probability
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| A good knowledge of set theory and of the classical formulae of combinatorial analysis is necessary (these specific matters are taught in the course entitlde 'elementary mathematics', Bloc 1, first semester) | |||||
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Planned learning activities and teaching methods :
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| Look at the information given for each part.
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Part 1 : Descriptive Statistics
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| The course is divided into three parts:
- Theory - Exercises - Learning of a statistical software The type of teaching for the theory part is ex-cathedra. The professor uses beamer projections or writes on the black boards. When slides are used, these will be available in advance on MyULg. The tutorials combine ex-cathedra presentation and individual work for the students. The statistical software will be taught mainly by self-learning but also during two practicals organised in the computer room of the mathematics department. |
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Introduction to probability
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| The learning activites are similar to those presentedin the first part, except that there is no statistical software activities in this second part.
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Mode of delivery (face-to-face ; distance-learning) :
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| look at the information indicated in the partims. | |||||
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Part 1 : Descriptive Statistics
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| The courses, the tutorials and the two practicals are given face-to-face over the second semester according to a timetable distributed to the students in the beginning of the academic year.
The theory lectures are recorded by means of the podcast equipment installed in the lecture room. The students may visualize these recordings when they want. |
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Introduction to probability
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| The delivery mode is again face-to-face. If required by the students, the recording of the lectures by means of the podcast equipment might be continued in this second part. | |||||
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Recommended or required readings :
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| Look at the informations given in the partims. | |||||
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Part 1 : Descriptive Statistics
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| Notes written in French (on the theory and on the exercises) will be sold to the students at the start of the academic year. These notes will also be available on line (via MyULg) | |||||
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Introduction to probability
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| Notes written in French (on the theory and on the exercises related to the contents of the second part) will be sold to the students and also put on line. | |||||
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Assessment methods and criteria :
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| The final mark is based on the marks attributed to the two following assessments (all taking place in May-June):
- written exam (theory and exercises) jointly on the contents from the two partims - practical exam on descriptive statistics in the computer room The computation of the final grade will be specified during the first lecture. The computation will be different whether the two separate marks are bigger or equal to 5/20 or not. In case at least one of the two marks is below 5/20, the global mark will not exceed 5/20. In case of absence at one part of the exam, the students will be given a mark of 0/20 for that part. |
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Part 1 : Descriptive Statistics
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| Bachelor in mathematics: look at the information written in the overall document.
Bachelor in computer sciences: the final mark is based on the marks attributed to the two following assessments (all taking place in May-June): - written exam on theory and exercises - practical exam in the computer room The computation of the final grade will be specified during the first lecture. The computation will be different whether the two separate marks are bigger or equal to 5/20 or not. In case at least one of the two marks is below 5/20, the global mark will not exceed 5/20. In case of absence at one part of the exam, the students will be given a mark of 0/20 for that part. |
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Introduction to probability
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| look at the general information.
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Work placement(s) :
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Organizational remarks :
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| None | |||||
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Part 1 : Descriptive Statistics
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| None | |||||
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Introduction to probability
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| None | |||||
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Contacts :
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| G.HAESBROECK, Institute of mathematics, Building B37, room 0/60, tel: 04/366-95-94, email: G.Haesbroeck@ulg.ac.be M. ERNST, Institute of mathematics, Building B37, email: m.ernst@ulg.ac.be | |||||
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Part 1 : Descriptive Statistics
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| The details are given above. | |||||
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Introduction to probability
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| The details are given above. | |||||