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| MATH1472-1 | Probability and Statistics I
- Part 1 : Descriptive Statistics
- Introduction to probability
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| Duration : | 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 : | Part 1 : Descriptive Statistics : Gentiane Haesbroeck
Introduction to probability : Gentiane Haesbroeck
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| Coordinator : | 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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Course contents :
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| In this course, basic concepts and techniques of descriptive statistics are taught. The learning of a statistical software is also included in the material of the course.
 | | 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. |
| | Introduction to probability |
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| This partim 2 is dedicated to an introduction to probability theory. |
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Learning outcomes of the course :
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| After this course, the student should be able to compute appropriate parameters and represent data by adequate diagrams in order to analyse data.
| | 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. |
| | Introduction to probability |
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| After this part, the student should be able to use correctly probability calculus. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Basic concepts of analysis and algebra are necessary. When more advanced notions will be useful, they will be explained beforehand.
| | Part 1 : Descriptive Statistics |
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| basic concepts of analysis and algebra taught in secondary school. |
| | Introduction to probability |
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| Set theory is necessary. |
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Planned learning activities and teaching methods :
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| The 15 hours of practicals will be consist of tutorials while the 10h of practicals will take place in the computer room of the mathematical Institute.
| | Part 1 : Descriptive Statistics |
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| The course is divided into three parts:
- Theory
- Tutorials (exercises)
- Practicals (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. Some practicals might be organised if computer rooms are available and if the schedule of the students allows it. |
| | Introduction to probability |
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| The courses (theory classes and tutorials) will be taught in an ex-cathedra fashion.
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Mode of delivery (face-to-face ; distance-learning) :
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| The courses and the tutorials/practicals are given over the second semester according to a timetable distributed to the students in the beginning of the academic year.
| | Part 1 : Descriptive Statistics |
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| The courses and the tutorials/practicals are given over the second semester according to a timetable distributed to the students in the beginning of the academic year. |
| | Introduction to probability |
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| The courses and the tutorials/practicals are given over the second semester, face-to-face, according to a timetable distributed to the students in the beginning of the academic year. |
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Recommended or required readings :
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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.
| | 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. |
| | Introduction to probability |
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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. |
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Assessment methods and criteria :
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| The final mark is a weighted mean of the marks attributed to the three following assessments (all ataking place in May-June):
- written exam on exercises
- oral exam on theory
- practical exam in the computer room
In case of absence at at least one part of the exam, the final grade will be set at 'Absent'.
| | Part 1 : Descriptive Statistics |
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| The final mark is based on the marks attributed to the three following assessments (all ataking place in May-June):
- written exam on exercises
- oral exam on theory
- practical exam in the computer room
In case of absence at at least one part of the exam, the final grade will be set at 'Absent'. |
| | Introduction to probability |
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| The final mark for this part will be based on the separate grades obtaided at an oral exam for the theory and at a written exam for the exercises.
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Work placement(s) :
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Organizational remarks :
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| None
| | Part 1 : Descriptive Statistics |
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| None |
| | 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
| | Part 1 : Descriptive Statistics |
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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 |
| | Introduction to probability |
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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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