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Education

Applied Mathematics and Biostatistics

Data

Official data in SubjectManager for the following academic year: 2022-2023

Course director

Number of hours/semester

lectures: 14 hours

practices: 0 hours

seminars: 28 hours

total of: 42 hours

Subject data

  • Code of subject: OBA-103-T
  • 2 kredit
  • Biotechnology MSc
  • Basic modul
  • autumn
Prerequisites:

-

Course headcount limitations

min. 1 – max. 200

Topic

Teaching the basics of math skills and techniques used in the laboratory work as well as statistical methods.

Lectures

  • 1. Introduction. Math basics: powers, exponents, logarithms - Dr. Grama László
  • 2. Physical quantities and units. Conversion of units - Dr. Grama László
  • 3. Concentrations - Dr. Grama László
  • 4. Dilutions - Dr. Grama László
  • 5. Spectrophotometry, radioactive decay, bimolecular interactions, centrifugation - Dr. Grama László
  • 6. Lab maths summary, test writing - Dr. Grama László
  • 7. Descriptive statistics 1: measures of the center and the spread of the data - Dr. Bugyi Beáta
  • 8. Descriptive statistics 2: data representation, box-whisker plots, histograms - Dr. Bugyi Beáta
  • 9. Normal distribution, hypothesis testing - Dr. Bugyi Beáta
  • 10. Hypothesis testing: Z test, t test - Dr. Bugyi Beáta
  • 11. Hypothesis testing: ANOVA - Dr. Bugyi Beáta
  • 12. Hypothesis testing: KHI2 test - Dr. Bugyi Beáta
  • 13. Test writing, Correlation, regression 1 - Dr. Bugyi Beáta
  • 14. Correlation, regresion 2 - Dr. Bugyi Beáta

Practices

Seminars

  • 1. Introduction. Math basics: powers, exponents, logarithms
  • 2. Introduction. Math basics: powers, exponents, logarithms
  • 3. Physical quantities and units. Conversion of units
  • 4. Physical quantities and units. Conversion of units
  • 5. Concentrations
  • 6. Concentrations
  • 7. Dilutions
  • 8. Dilutions
  • 9. Spectrophotometry, radioactive decay, bimolecular interactions, centrifugation
  • 10. Spectrophotometry, radioactive decay, bimolecular interactions, centrifugation
  • 11. Lab maths summary, test writing
  • 12. Lab maths summary, test writing
  • 13. Descriptive statistics 1: measures of the center and the spread of the data
  • 14. Descriptive statistics 1: measures of the center and the spread of the data
  • 15. Descriptive statistics 2: data representation, box-whisker plots, histograms
  • 16. Descriptive statistics 2: data representation, box-whisker plots, histograms
  • 17. Normal distribution, hypothesis testing
  • 18. Normal distribution, hypothesis testing
  • 19. Hypothesis testing: Z test, t test
  • 20. Hypothesis testing: Z test, t test
  • 21. Hypothesis testing: ANOVA
  • 22. Hypothesis testing: ANOVA
  • 23. Hypothesis testing: KHI2 test
  • 24. Hypothesis testing: KHI2 test
  • 25. Test writing, Correlation, regression 1
  • 26. Test writing, Correlation, regression 1
  • 27. Correlation, regresion 2
  • 28. Correlation, regresion 2

Reading material

Obligatory literature

Literature developed by the Department

Will be published on Teams, Moodle or PotePedia.

Notes

Recommended literature

Conditions for acceptance of the semester

Maximum of 25 % absence allowed

Mid-term exams

Students will write 2 midterm tests from the 2 major sections of the material: lab maths and statistics. Two retake opportunities will be provided to those who do not pass these tests.

Making up for missed classes

None.

Exam topics/questions

Midterm tests and their retakes consist of problem solving and calculations from the main topics of the course.

Examiners

Instructor / tutor of practices and seminars

  • Dr. Bugyi Beáta
  • Dr. Grama László
Rólunk