Study programme 2020-2021Français
Introduction aux statistiques biomédicales
Programme component of Bachelor's in Pharmacy à la Faculty of Medicine and Pharmacy

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what special Covid-19 assessment methods are possibly planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
UM-B1-PHARMA-015-MCompulsory UELELUBRE ChristopheM101 - FMP - Service du Doyen
  • LELUBRE Christophe

of instruction
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français15000022.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
M-DOYM-051Introduction to biomedical statistics150000Q1100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • 1. Pharmaceutical expertise: Use a foundation of concepts and knowledge in health sciences and pharmaceutical sciences.
    • Understand and apply mathematical translations of large models and chemical and/or biological phenomena through abstract reasoning
    • Understand and use different graphical representations of numerical values and their relationships
  • 2. Scientific method: Solve pharmaceutical problems using their knowledge and critical mind.
    • Understand and apply the basic principles of reasoning (obtaining data, analysis, synthesis, comparison, the rule of three, syllogism, analogy, Boolean logic, etc.)
    • Understand and use statistical methods
    • Develop a critical, practical and analytical mind
    • Manage doubt and uncertainty
  • 3. Communication: Communicate in an appropriate, efficient, rigorous and respectful way in a professional perspective.
    • Use a rich vocabulary linking concepts and words accurately
    • Share knowledge and information
  • 5. Quality: Assess themself, expand their knowledge and adapt their attitude.
    • Research, read, interpret, and critique a scientific paper with sufficient knowledge of scientific English

Learning Outcomes of UE

Learning outcomes include : - Understanding the most frequent tools used in descriptive statistics and how to use them practically; - Interpreting graphical outputs such as box plots; - Understanding basic principles of correlation (Pearson, Spearman) and linear regression; - Being able to compute confidence intervals and understand their meaning - Understanding the basis of inferential statistics, which is a fundamental prerequisite before taking more advanced statistical courses.

Content of UE

Definition and aims of biostatistics. Variability in medicine. Types of variables. Univariate descriptive statistics (localisation and dispersion parameters) and graphical output. Bivariate descriptive statistics (linear correlation and simple linear regression). Frequency and probability of event. Elements of combinatorics. Conditional probability and Bayes theorem. Random variable (discrete and continuous). Probability density function. Central limit theorem. Binomial and Poisson laws. Normal and Z law. Use of statistical tables. Confidence interval for means and percentages.

Prior Experience

Not applicable

Type of Assessment for UE in Q1

  • Written examination

Q1 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

  • Written examination

Q3 UE Assessment Comments

Not applicable.

Type of Resit Assessment for UE in Q1 (BAB1)

  • Written examination

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
  • Cours magistraux

Mode of delivery

AAMode of delivery
  • Mixed

Required Reading


Required Learning Resources/Tools

AARequired Learning Resources/Tools
M-DOYM-051Not applicable

Recommended Reading


Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
M-DOYM-051Not applicable

Other Recommended Reading

AAOther Recommended Reading
M-DOYM-051* Thierry Ancelle, Statistique - Epidémiologie (4è Edition). Maloine, 2017 (également conseillé pour les cours de statistique et épidémiologie de BA2). * Jean Bouyer, Méthodes statistiques - Médecine - Biologie. Vuibert, 2017 (également conseillé pour les cours de statistique et épidémiologie de BA2).

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 09/07/2021
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