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FF506: Mathematics, statistics and physics for biology and pharmacy (10 ECTS)

STADS: 07007801

Level
Bachelor course

Teaching period
The course begins in the autumn semester and continues in the spring semester.

Teacher responsible
No responsible teachers found, contact the department if necessary

Timetable
Group Type Day Time Classroom Weeks Comment
Common I Monday 10-12 U110 03-05
Common I Monday 10-12 U55 06-11
Common I Wednesday 13-15 U55 06
S8 TL Tuesday 14-17 Lab 8 & 9 07-09
S8 TE Friday 08-10 U25a 05
S8 TE Friday 08-10 U49b 06-12
S10 TE Monday 14-16 U155 05-12
S10 TL Wednesday 14-17 Lab 8 & 9 07-08
S10 TL Wednesday 15-18 Lab 8 & 9 09
S11 TE Thursday 12-14 U131 05
S11 TE Thursday 12-14 U49d 06-12
S11 TL Friday 14-17 Lab 8 & 9 07-09
S12 TL Wednesday 09-12 Lab 8 & 9 07-08
S12 TL Wednesday 08-11 Lab 8 & 9 09
S12 TE Thursday 14-16 U155 05,07-12
S12 TE Thursday 14-16 U30a 06
S13 TL Thursday 09-12 Lab 8 & 9 07-09
S13 TE Friday 10-12 U20 05-12
S18 TE Tuesday 14-16 U144 05
S18 TE Tuesday 14-16 U49c 06-12
S18 TL Friday 09-12 Lab 8 & 9 07-09
S28 TE Tuesday 08-10 U154 05-09,11-12
S28 TE Tuesday 10-12 U154 10
S28 TL Thursday 14-17 Lab 8 & 9 07-09
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Revison of timetable:
: Laboratorietimerne for hold S8 i FF506 om tirsdagen fra kl. 14-17 i ugerne 07-09, har følgende ændringer: Lokale ændret fra til FYSIK lab

Prerequisites:
None

Academic preconditions:
None

Course introduction
The course gives an introduction to a range of subjects in basic mathematics and physics. The focus is on topics that are relevant for pharmacists and biologists. The course will provide a conceptual understanding of physical phenomena and develop the ability to mathematically treat simple systems. Students on the course will be trained in elementary methods and techniques in differential calculus, building on material familiar to the students from the gymnasium. Experimental exercises and demonstrations constitute an integrated part of the course. The participants will learn the basic methods for statistical description and analysis in relation to biological research. The participants will learn how to use a statistical software package for analyzing data

Expected learning outcome
After completing the course the student is expected to be able to:

  • apply methods and results from differential and integral calculus of functions of one real variable to solve mathematical problems within the scope of the syllabus of the course.
  • utilize graphics and summary methods for descriptive data analysis.
  • test simple statistical hypotheses.
  • apply simple mathematical tools to solve a physical problem and evaluate the validity of own computed results.
  • perform physical experiments, describe the outcome and interpret the results of these experiments.
  • apply physical principles and concepts to estimate the behavior of a physical system.
  • identify the physical laws and methods that should be applied to a given physical problem.
Subject overview
  1. Functions: Polynomials, logarithms, exponentials and inverse trigonometric functions.
  2. Calculus: Differential and integral calculus, Taylor polynomials and limits.
  3. Differential equations: 1st order linear and separable and 2nd order linear differential equations.
  4. Statistics: The foundation for statistical considerations.
  5. Descriptive statistics (tables, summary statistics and graphics).
  6. Statistical test methods: t-test, chi-square-test, oneway ANOVA, simple linear regression.
  7. Mechanics: Kinematics, newtons laws, statics, mechanical energy, Hookes law, harmonic oscillations.
  8. Fluids and Transport: Hydrostatics, pressure, buoyancy, fluids, viscosity, diffusion, brownian motion.
  9. Thermodynamics: Heat, work, internal energy, the 1st law of thermodynamics, ideal gasses, osmosis, changes in ideal gasses
  10. Electromagnetism and Optics: Electrical and magnetic fields, light, reflection, refraction, absorbtion (Lambert-Beers law), polarization, optical activity.

Laboratory exercise 1: Brownian Motion
Laboratory exercise 2: Ideal gasses
Laboratory exercise 3: Optical activity

PC exercises statistics with R



Literature
There isn't any litterature for the course at the moment.

Website
This course uses e-learn (blackboard).

Prerequisites for participating in the exam
None

Assessment and marking:
  1. Mandatory assignments (5 ECTS). Pass/fail, internal evaluation by teacher.  (07007812)
  2. Lab. work. Pass/fail, internal evaluation by teacher (1 ECTS). (07007822)
  3. Oral exam. Pass/fail, internal examiner (4 ECTS). (07007802)

Reexam in the same exam period or immediately thereafter,

The mode of exam at the reexamination may differ from the mode of exam at the ordinary exam.



Expected working hours
The teaching method is based on three phase model.
Intro phase: 50 hours
Skills training phase: 59 hours, hereof:
 - Tutorials: 44 hours
 - Laboratory exercises: 15 hours

Educational activities Study phase: 15 hours

Language
This course is taught in Danish or English, depending on the lecturer.

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.