Biometrics for Dentists

Adatok

A Tantárgybejelentőben megadott hivatalos adatok az alábbi tanévre: 2025-2026

Tematika

The aim of the course is: reviewing and processing data and characterization using graphical and numerical tools, probability and statistical conclusion/decision, basic statistical methods commonly used in medicine and medical practice.

The other goal is introducing and practising the basics of statistical thinking. The skills and competences can be developed with statistics in scientific background and daily work of medicine. Analytical and critical thinking are of high importance in medical decision making, and there is also an opportunity to develop these skills within the subject.

Előadások

• 1. Introduction (Biometrics and Medical Sciences). Probability and relative frequency. - Kőnigné Péter Anikó
• 2.

  Experiment designs and types of variables

  - Makszin Lilla
• 3.

  Descriptive statistics

  - Makszin Lilla
• 4.

  Probability calculation and discrete distributions.

  - Dergez Tímea
• 5. Continuous probability distributions-normal distribution. - Kőnigné Péter Anikó
• 6. Statistical estimations. Confidence interval for the expected value. - Dergez Tímea
• 7. Principle of hypothesis testing. The one sample and the paired samples t tests. - Kőnigné Péter Anikó
• 8. The confidence interval and the hypothesis testing. Type I and type II errors. - Dergez Tímea
• 9. The independent samples t test. The power of the test. - Kőnigné Péter Anikó
• 10. The non-parametric tests: Sign-, Wilcoxon-, Mann-Whitney tests. - Dergez Tímea
• 11. Linear regression and correlation. - Dergez Tímea
• 12.

  The evaluation of frequency data: Chi-squared test and Fisher's exact test. Special applications.

  - Makszin Lilla
• 13. The principle of the ANOVA. - Dergez Tímea
• 14. Summary of the hypothesis testing methods. - Kőnigné Péter Anikó

Gyakorlatok

• 1. Relative frequency and probability, thinking models (deterministic and stochastic models).
• 2. Types of data and their representation.
• 3.

  Exploring data by numbers - descriptive statistics

• 4.

  Probability calculation-Binomial and Poisson distribution.

• 5. Normal distribution. The distribution of the sample mean.
• 6. Estimations. The confidence interval of the expected value.
• 7. 1st midterm test. The hypothesis testing - the one sample (and the paired samples) t tests.
• 8. Two independent samples t test. The Type one and Type two errors.
• 9. Nonparametric tests.
• 10. The linear regression and correlation.
• 11. Contingency tables - the chi-squares test, Fisher's exact test.
• 12. Summary.
• 13. Practice.
• 14. 2nd midterm test.

Szemináriumok

A tananyag elsajátításához szükséges segédanyagok

Kötelező irodalom

Saját oktatási anyag

Moodle, PotePedia files

Jegyzet

Moodle electronic notes

Joseph Belágyi: Medical Biometry

Sára Jeges: Biometry

L. Pótó: Biometrics. Workbook for the Practices, Pécs, 2020

Ajánlott irodalom

1. D.S. Moore, G.P. McCabe: Introduction to the Practice of Statistics, 5th ed., W.H. Freeman 2005

2. D. Yates, D.S. Moore, D.S. Starnes: The Practice of Statistics (TI-83/89 Graphing Calculator Enhanced) 2/e, 2003, W.H. Freeman

3. W.G. Rees: Essential Statistics, Chapman and Hall, 1992

A félév elfogadásának feltételei

Practice:

To complete the practice, students must write two midterm tests, both with a minimum of 60%, and take the short tests at the beginning of the class. The combined result of the two midterm tests and the weekly tests must be 50%.

If a student scores less than 60% in any of the midterm tests, he/she will be given a one-time make-up midterm test. A maximum of three absences from practice is allowed.

Exam:

The exam is oral and based on the lectures and practices materials, focusing on the theoretical background. The exam questions will be available in the Moodle.

Final grade:

The final grade will be determined by the practice and oral exam results with a weighting of 50-50%.

Félévközi ellenőrzések

There are two midterm tests during the semester and short tests at the beginning of all practices.

Távolmaradás pótlásának lehetőségei

Retake class.

Vizsgakérdések

Themes of theoretical part:

1. The main goals / potential results of learning biometrics/biostatistics.

2. The key feature of the statistical thinking - The probability.

3. The idea of the probability distribution - discrete distributions.

4. The basic principles of statistical thinking - from the data to the decision: size of the sample, representativity, lurking variables.

5. Types of the data (variables) and displaying them with graphs.

6. Graphical and numerical characterization of the sample and the population

7. Numerical description of continuous data: five number and three number descriptions.

8. The idea of the probability distribution - continuous distributions.

9. The normal distribution, the central limit theorem.

10. Statistical estimation: point estimation and interval estimation.

11. The confidence interval of the population mean

12. The basic idea of hypothesis testing

13. The one sample and the paired t-test

14. Comparing the confidence interval and the hypothesis testing.

15. The risk of errors and the power of a test.

16. The two (independent) samples t-test.

17. Connection between two variables - in case of continuous variables.

18. Connection between two variables - in case of categorical variables.

19. Special application of the contingency table, qualification of a diagnostic test (sensitivity, specificity, predictive values).

20. Nonparametric tests in case of one-, paired sample

21. Nonparametric tests in case of independent samples.

22. The principle of the Analysis of Variance (ANOVA).

Vizsgáztatók

• Dergez Tímea
• Kőnigné Péter Anikó
• Makszin Lilla

Gyakorlatok, szemináriumok oktatói

• Dergez Tímea
• Kőnigné Péter Anikó
• KURZUSHOZ RENDELT OKTATÓ
• Makszin Lilla
• Mátrai Péter