4.00 credits

15.0 h + 15.0 h

Q1

Teacher(s)

Bugli Céline;

Language

French

Main themes

Main themes: - Steps of a statistical data analysis with a statistical software - Classes of statistical software - Statistical graphics: main classes of graphics and efficient use - Basic statistical analysis with "point and click" statistical software. Data cleaning. - Programming in the R language. - Programming in SAS.

Learning outcomes

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At the end of this course, the students will have gain a critical view of the different classes of statistical software available on the market and basic culture on statistical algorithms and graphics. They will also be able to realise basic statistical analysis with different software (SAS, R, Excel, SPSS, JMP) and write programs in the R and SAS programming languages. |

Content

Lecture: Steps in statistical analysis of computer data. Introduction to the different classes of statistical software. Graphical presentation of data. Introduction to statistical software, Introduction to the use of the computer room. Case studies of data set analysis using basic statistical methods. Generation of random numbers. Numerical problems encountered in regression. Introduction to R and SAS. Communication between different software and languages (R, SAS, etc...).

Exercises: SAS and R programming exercises. Case studies with SPSS or JMP software.

Exercises: SAS and R programming exercises. Case studies with SPSS or JMP software.

Teaching methods

The course consists of lectures with demonstrations of statistical software and software use exercises sessions designed to give the student maximum autonomy: each student works at his own pace on the basis of evolving documents.

The lectures will be given in co-modal (simultaneous transmission of the course given in auditorium on Teams) and the practical work will be given in face-to-face only.

The modalities foreseen will evolve according to the health situation.

The lectures will be given in co-modal (simultaneous transmission of the course given in auditorium on Teams) and the practical work will be given in face-to-face only.

The modalities foreseen will evolve according to the health situation.

Evaluation methods

In this course, students are evaluated in two ways:

The written, open book and computer-based exam (if the sanitary situation allows it) consists of solving basic statistical case studies with SAS Enterprise Guide and SPSS (or JMP) software, and SAS and R programming questions.

Please note that the mandatory assignments are to be completed during the first quarter of the academic year according to a schedule that will be communicated at the beginning of the course. In case of non submission of an assignment, the student will have 0 on his first exam attempt. However, with the professor's permission, the student may take an additional question to make up the grade in the second session. The student's request to retake the assignment must be made BEFORE the start of the exam session and will only be considered if the assignment has not been has not been returned or is failed (less than 50%).

- continuous assessment including two compulsory assignments to be handed in at the end of the term according to a schedule set at the beginning of the term (15% of the final grade)
- a written exam on computer during the exam's session (85% of the final grade)

The written, open book and computer-based exam (if the sanitary situation allows it) consists of solving basic statistical case studies with SAS Enterprise Guide and SPSS (or JMP) software, and SAS and R programming questions.

Please note that the mandatory assignments are to be completed during the first quarter of the academic year according to a schedule that will be communicated at the beginning of the course. In case of non submission of an assignment, the student will have 0 on his first exam attempt. However, with the professor's permission, the student may take an additional question to make up the grade in the second session. The student's request to retake the assignment must be made BEFORE the start of the exam session and will only be considered if the assignment has not been has not been returned or is failed (less than 50%).

Online resources

Faculty or entity

**LSBA**

#### Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme

Sigle

Credits

Prerequisites

Learning outcomes

Master [120] in Statistics: General

Master [120] in Agricultural Bioengineering

Master [120] in Mathematics

Master [120] in Environmental Bioengineering

Master [120] in Statistics: Biostatistics

Master [120] in Biomedical Engineering

Approfondissement en statistique et sciences des données

Minor in Statistics, Actuarial Sciences and Data Sciences

Master [120] in Forests and Natural Areas Engineering

Master [120] in Chemistry and Bioindustries

Certificat d'université : Statistique et sciences des données (15/30 crédits)

Master [120] in Mathematical Engineering

Master [120] in Data Science : Statistic