MM556: Mathematics and statistics for pharmacy
Internal Course Code
Comment
Entry requirements
The course cannot be taken by students who have passed FF502, FF506, MM536, AI503, MM554, MM558, MM572, FT501 or KE551, or if the course is included as a mandatory part of their study program.
However, this course can only be taken if it:
- is a constituent part of your programme
- is a specified recommendation for elective ECTS in your programme
- is part of a specified transitional arrangement ('overgangsordning') for a course you have not yet passed
Academic preconditions
Students taking the course are expected to:
- be able to solve simple arithmetic and algebra problems (e.g. calculate proportions and percentages, combining like terms, solving linear equations with a single unknown, etc.)
- be able to handle special functions (i.e. linear, exponential, logarithmic, polynomials, trigonometric)
- be able to solve problems involving differentiation and integration.
- know multiplying and dividing monomials, binomials, and polynomials.
Course introduction
iopharmaceutics as well as social pharmacy, drug administration and pharmaceutical statistics, require a good understanding of mathematics and their applications. As a result, most biological systems are explored and explained using mathematical models. Therefore, the purpose of the course is to provide the students with the fundamental tools to understand and solve mathematical problems with emphasis on pharmaceutically relevant problems. The course will provide the necessary analytical skills for differentiation, integration and to solve differential equations, as well as basic notions on statistics, while the students will also learn the application of numerical methods, such as linear and Taylor approximations, Riemann sums or Euler’s method to solve differential equations. These numerical techniques are particularly important in areas such as pharmacokinetics and physical chemistry. To apply these numerical methods, the students will become familiar with the free-open source software R. Students will then be trained on the basic methods in pharmaceutical statistics, which will give them elements to judge the validity of research projects relevant to pharmacy. Furthermore, these methods will provide the students with the basic tools to analyse results from experiments and pharmaceutical trials.
The course gives an academic basis for studying topics relevant to analytical spectroscopy, physical chemistry and molecular biology, all of which are part of the degree.
Expected learning outcome
The learning objectives of the course are that the student demonstrates the ability to:
- demonstrate
the ability to identify the appropriate functions to describe simple
processes relevant to pharmaceutical applications. - judge which methods are appropriate to solve (either analytically or using numerical methods)
- understand
and consequently disseminate both in written form and orally scientific
articles/book chapters from the research area. - apply and transfer methods from the presented applications to new problems, also in the context of other subjects.
- implement solutions based on the analytical and numerical methods learned in class using the programming language R.
Content
The following main topics are contained in the course:
- Sets, properties of functions and special functions (linear, logarithmic, exponential, polynomials, rational, trigonometric)
- Differentiation and applications of differentiation
- Linear and Taylor approximations
- Integrals and integration methods
- Methods to solve first and second order differential equations
- Basic notions of probability and distributions
- Descriptive statistics (exploratory data analysis)
- Methods for hypothesis testing: t-test, chi-square test, ANOVA, simple linear regression.
Literature
Examination regulations
Exam element a)
Timing
Tests
Portfolio
EKA
Assessment
Grading
Identification
Language
Examination aids
To be announced during the course
ECTS value
Additional information
- Three mandatory tests. Count 60 % of the total evaluation.
Allowed exam aids: Open book, only R as software - Eight quizzes. Count 20 % of the total evaluation.
- Four group exercises. Count 20 % of the total evaluation
The re-exam will be changed to an oral exam, if 5 or fewer students are enrolled.
- Duration: 30 minutes (including side questions)
- Topics are given before the exam date.
- Students draw topic on the exam date.
- Students have 30 minutes preparation time before oral exam.
Indicative number of lessons
Teaching Method
Planned lessons:
Total number of planned lessons: 66
Hereof:
Common lessons in classroom/auditorium: 28
Team lessons in classroom: 38
The purpose of the team lessons is to present and discuss assigned problems, as well as review selected topics and discuss any difficulties you may have with your instructor. Group exercises and exams are scheduled during team lessons.
During the common lessons, the lecturer will review concepts, methods, and relevant examples. Lectures typically include classroom discussions, the use of student response systems, peer-to-peer discussion, and working on short exercises by yourself or with others.
Other planned teaching activities:
- Solving practice exercises.
- Reading handouts and other material.
- Answering graded quizzes on the material they have read.
- Investigating and discussing the terms and concepts they are struggling with.