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Mathematical and Biostatistical Foundation of Biotechnology

Data

Official data in SubjectManager for the following academic year: 2024-2025

Course director

Number of hours/semester

lectures: 28 hours

practices: 28 hours

seminars: 14 hours

total of: 70 hours

Subject data

  • Code of subject: OTN-MBFB-T
  • 5 kredit
  • Biotechnology BSc
  • Basic Module modul
  • spring
Prerequisites:

OTN-MBBS-T finished

Course headcount limitations

min. 5 – max. 50

Topic

Main topics of the subject: Principles of descriptive and inferential statistics; models, planning of experiments, presentation, analysis and evaluation of data.

Principles of descriptive statistics. Data, types of data, data analysis and evaluation. Presentation of data on graphs, diagrams. Probability, random variable, discrete and continuous statistical distributions. Principles of inferential statistics. Statistical hypothesis testing. Parametric and non-parametric approaches. Correlation and regression analysis.

Statistical software packages and support: problem-solving with Microsoft Excel, an overview of other tools.

Lectures

  • 27.

    Revision, consultation, end semester test.

    - Bódis Emőke
  • 28.

    Revision, consultation, end semester test.

    - Bódis Emőke
  • 26.

    Workshop. Discussion of case studies and Students' projects.

    - Karádi Kristóf Kálmán
  • 21.

    Regression analysis. Least squares principle.

    - Csepregi Kristóf
  • 22.

    Regression analysis. Least squares principle.

    - Csepregi Kristóf
  • 23.

    Correlation analysis. Rank correlation.

    - Csepregi Kristóf
  • 25.

    Workshop. Discussion of case studies and Students' projects.

    - Karádi Kristóf Kálmán
  • 24.

    Correlation analysis. Rank correlation.

    - Csepregi Kristóf
  • 20.

    Analysis of variance

    - Bukovics Péter
  • 19.

    Analysis of variance

    - Bukovics Péter
  • 18.

    The chi-square test and its applications: goodness of fit test and test for independence.

    - Bukovics Péter
  • 17.

    The chi-square test and its applications: goodness of fit test and test for independence.

    - Bukovics Péter
  • 16.

    Revision, consultation, midterm test.

    - Karádi Kristóf Kálmán
  • 15.

    Revision, consultation, midterm test.

    - Karádi Kristóf Kálmán
  • 14.

    Nonparametric methods: Wilcoxon test, Mann-Whitney U test.

    - Bukovics Péter
  • 13.

    Nonparametric methods: Wilcoxon test, Mann-Whitney U test.

    - Bukovics Péter
  • 12.

    Analysis of the means with t-test.

    - Bukovics Péter
  • 11.

    Analysis of the means with t-test.

    - Bukovics Péter
  • 9.

    Hypothesis testing: the u-test.

    - Karádi Kristóf Kálmán
  • 10.

    Hypothesis testing: the u-test.

    - Karádi Kristóf Kálmán
  • 8.

    Statistical hypothesis testing. Hypothesis testing: the sign test.

    - Karádi Kristóf Kálmán
  • 7.

    Statistical hypothesis testing. Hypothesis testing: the sign test.

    - Karádi Kristóf Kálmán
  • 6.

    Continuous probability distributions. Normal and lognormal distribution.

    - Trombitás Norbert
  • 5.

    Continuous probability distributions. Normal and lognormal distribution.

    - Trombitás Norbert
  • 4.

    The characteristics of population and sample: mean, dispersion and standard error. The elements of standard error calculation. Probability and probability distribution.

    - Bódis Emőke
  • 3.

    The characteristics of population and sample: mean, dispersion and standard error. The elements of standard error calculation. Probability and probability distribution.

    - Bódis Emőke
  • 1.

    Introduction. The applied statistical models. Planning and carrying out an experiment. Data analysis, frequency distributions and histogram

    - Bódis Emőke
  • 2.

    Introduction. The applied statistical models. Planning and carrying out an experiment. Data analysis, frequency distributions and histogram

    - Bódis Emőke

Practices

  • 28.

    Revision, consultation, end semester test.

    - Bódis Emőke
  • 26.

    Workshop. Discussion of case studies and Students' projects.

    - Karádi Kristóf Kálmán
  • 27.

    Revision, consultation, end semester test.

    - Bódis Emőke
  • 25.

    Workshop. Discussion of case studies and Students' projects.

    - Karádi Kristóf Kálmán
  • 22.

    Regression analysis. Least squares principle.

    - Csepregi Kristóf
  • 23.

    Correlation analysis. Rank correlation.

    - Csepregi Kristóf
  • 24.

    Correlation analysis. Rank correlation.

    - Csepregi Kristóf
  • 20.

    Analysis of variance

    - Bukovics Péter
  • 21.

    Regression analysis. Least squares principle.

    - Csepregi Kristóf
  • 17.

    The chi-square test and its applications: goodness of fit test and test for independence.

    - Bukovics Péter
  • 18.

    The chi-square test and its applications: goodness of fit test and test for independence.

    - Bukovics Péter
  • 19.

    Analysis of variance

    - Bukovics Péter
  • 14.

    Nonparametric methods: Wilcoxon test, Mann-Whitney U test.

    - Bukovics Péter
  • 15.

    Revision, consultation, midterm test.

    - Karádi Kristóf Kálmán
  • 16.

    Revision, consultation, midterm test.

    - Karádi Kristóf Kálmán
  • 13.

    Nonparametric methods: Wilcoxon test, Mann-Whitney U test.

    - Bukovics Péter
  • 12.

    Analysis of the means with t-test.

    - Bukovics Péter
  • 11.

    Analysis of the means with t-test.

    - Bukovics Péter
  • 10.

    Hypothesis testing: the u-test.

    - Karádi Kristóf Kálmán
  • 9.

    Hypothesis testing: the u-test.

    - Karádi Kristóf Kálmán
  • 8.

    Statistical hypothesis testing. Hypothesis testing: the sign test.

    - Karádi Kristóf Kálmán
  • 7.

    Statistical hypothesis testing. Hypothesis testing: the sign test.

    - Karádi Kristóf Kálmán
  • 6.

    Continuous probability distributions. Normal and lognormal distribution.

    - Trombitás Norbert
  • 5.

    Continuous probability distributions. Normal and lognormal distribution.

    - Trombitás Norbert
  • 4.

    The characteristics of population and sample: mean, dispersion and standard error. The elements of standard error calculation. Probability and probability distribution.

    - Bódis Emőke
  • 3.

    The characteristics of population and sample: mean, dispersion and standard error. The elements of standard error calculation. Probability and probability distribution.

    - Bódis Emőke
  • 2.

    Introduction. The applied statistical models. Planning and carrying out an experiment. Data analysis, frequency distributions and histogram.

    - Bódis Emőke
  • 1.

    Introduction. The applied statistical models. Planning and carrying out an experiment. Data analysis, frequency distributions and histogram.

    - Bódis Emőke

Seminars

  • 13.

    Workshop. Discussion of case studies and Students' projects.

    - Karádi Kristóf Kálmán
  • 14.

    Revision, consultation, end semester test.

    - Bódis Emőke
  • 11.

    Regression analysis. Least squares principle.

    - Csepregi Kristóf
  • 12.

    Correlation analysis. Rank correlation.

    - Csepregi Kristóf
  • 8.

    Revision, consultation, midterm test.

    - Karádi Kristóf Kálmán
  • 9.

    The chi-square test and its applications: goodness of fit test and test for independence.

    - Bukovics Péter
  • 10.

    Analysis of variance

    - Bukovics Péter
  • 7.

    Nonparametric methods: Wilcoxon test, Mann-Whitney U test.

    - Bukovics Péter
  • 6.

    Analysis of the means with t-test.

    - Bukovics Péter
  • 5.

    Hypothesis testing: the u-test.

    - Karádi Kristóf Kálmán
  • 4.

    Statistical hypothesis testing. Hypothesis testing: the sign test.

    - Karádi Kristóf Kálmán
  • 3.

    Continuous probability distributions. Normal and lognormal distribution.

    - Trombitás Norbert
  • 2.

    The characteristics of population and sample: mean, dispersion and standard error. The elements of standard error calculation. Probability and probability distribution.

    - Bódis Emőke
  • 1.

    Introduction. The applied statistical models. Planning and carrying out an experiment. Data analysis, frequency distributions and histogram.

    - Bódis Emőke

Reading material

Obligatory literature

Homepage of the Department of Biophysics:

https://aok.pte.hu/en/egyseg/10/oktatasi-anyagok

Literature developed by the Department

Homepage of the Department of Biophysics:

https://aok.pte.hu/en/egyseg/10/oktatasi-anyagok

Notes

Homepage of the Department of Biophysics:

https://aok.pte.hu/en/egyseg/10/oktatasi-anyagok

Recommended literature

Statistics Openstax, ISBN-10: 1-947172-05-0, ISBN-13: 978-1-947172-05-0

Allan G. Bluman: Elementary statistics, ISBN 978–0–07–338610–2

Myra L- Samuels, Jeffrey A. Witmer, Andrew A. Schaffner: Statistics for the life sciences, ISBN-13: 978-1-292-10181-1

James Stewart, Troy Day: Biocalculus, ISBN-13: 978-1-133-10963-1

J. Pezzullo: Biostatistics for dummies, 2013, Wiley, ISBN 978-1-118-55399-2

Conditions for acceptance of the semester

none

Mid-term exams

The grade is based on the average result of the two tests written during the semester (expected dates: week 7 and week 14).

Grading policy:

< 60% (1, fail)

60 ≤ result < 70% (2, satisfactory)

70 ≤ result < 80% (3, average)

80 ≤ result < 90% (4, good)

90 ≤ result (5, excellent)

In case of a failed exam, the result can be improved based on the rules of the Code of Studies and Examinations.

Making up for missed classes

The opportunity to make up for absence can be discussed with the course leader.

Exam topics/questions

Principles of descriptive statistics. Data, types of data, data analysis and evaluation. Presentation of data on graphs, diagrams.

Probability, random variable, discrete (binomial) and continuous (normal, standard normal) statistical distributions.

Principles of inferential statistics. Statistical hypothesis testing, errors in the decision, family-wise error rate. Overview of parametric and non-parametric approaches.

Parametric approaches 1. (z-, and t-test)

Parametric approaches 2. (analysis of variance, F-test, ANOVA, posthoc tests (Tukey, Scheffe, Bonferroni))

Nonparametric approaches 1. (sign test, Wilcoxon, Mann-Whitney)

Nonparametric approaches 2. (Kruskal-Wallis, Friedman)

Correlation analysis. Scatter plot, correlation coefficient, the significance of the correlation coefficient, rank, rank correlation.

Regression analysis 1. Line of best fit, regression line equation. Coefficient of determination, the significance of R2, residual plots.

Regression analysis 2. Nonlinear regression.

CHI-squared test (goodness of fit, independence, homogeneity).

Examiners

  • Bódis Emőke
  • Bugyi Beáta
  • Karádi Kristóf Kálmán

Instructor / tutor of practices and seminars

  • Bódis Emőke
  • Bugyi Beáta
  • Bukovics Péter
  • Csepregi Kristóf
  • Karádi Kristóf Kálmán
  • Trombitás Norbert
Rólunk