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Medical Statistics
2020/2021, 2nd semester

obligatory course

COURSE DATA

Course Title: Medical statistics
LECTURE: 1 hour per week; Tuesday 3 pm - 4 pm online YouTube-stream
  • Credits: 1
  • Course code: AOK-OMK107
  • Assessment: end-semester exam

PRACTICE: 2 hours per week - MS Teams channels;  in case of turn to contact education in the classrooms of the Small Education Building
  • Credits: 2
  • Course code: AOK-OMK108
  • Assessment: term mark

AIM OF THE COURSE

The course aims to provide basic practical knowledge of biostatistics, the use, and interpretation of the most frequently used basic biostatistical methods used in medical research with the use of statistical software. With a conceptual understanding of data and data collection, we introduce techniques of data processing, representation, and interpretation. We cover topics of trend analysis, use of hypotheses, frequently used statistical tests, and their applications. Students will be able to state hypotheses according to the given experimental design, formulate the database, characterize the distribution of variables according to their type. Students will know the methods of the most often used hypothesis tests, they will be able to find the appropriate methods to test their hypotheses, and interpreting the results of computer programs and/or scientific papers. They will be able to decide when to ask for the help of a statistician.

REQUIREMENTS FOR THE SUCCESSFUL COMPLETION OF THE COURSE

PRACTICE
Attendance of the practice is obligatory. Participating in the practical sessions under the “Study Guide of the Faculty of Medicine”. Maximum 3 absences are allowed.

Forms of testing:

  • The students perform quizzes almost every week at the beginning of the practices from the topics of the previous weeks (practical; theoretical questions). The sum of these quizzes gives a maximum of 10% of the total practical points.
  • The students have to perform two tests this is the maximum 90% points of the total practical points. Both tests contain two parts:
    • theoretical test (5% - 5%)
    • practical test (40% - 40%)

   All the quizzes and tests will be CooSpace-tests.

Make-up possibilities:

  • Everybody is obligated to attend those practices in which are registered in Neptun. Practices are not replaceable.
  • Quizzes cannot be made up or retake.
  • Makeup or retake one of the tests is possible in the last week of the semester. The new points overwrite the previous test-result.

Practical mark
The practical mark is calculated based on the given practical points during the semester, according to the following table:

Accomplishment (%)    Mark

  • 0% – 50%                failed (1)
  • 50,01% – 62,50%    passed (2)
  • 62,51% – 75%         accepted (3)
  • 75,01% – 87,50%    good (4)
  • 87,51% – 100%       very good (5)


LECTURE

The end semester exam:
Students who fail to meet the requirements of practice (no mark or mark 1) cannot take the examination.
Students take a computer-aided (CooSpace) multiple-choice test examination at the end of the semester based on the topics of theory and practice.
Students have to sign up for the examination through the Neptun system. Repetition of examinations is according to the general regulations of the Study and the Examination Requirements of the University.
At the examination, a maximum of 20 points can be achieved.
Grades of the examination are determined as follows:

  • 0–9 points: failed (1)
  • 10–12 points: passed (2)
  • 13–15 points: accepted (3)
  • 16–17 points: good (4)
  • 18–20 points: excellent (5)

TOPICS

  1. Data description. Types of data, displaying data. Sample characteristics. (categorical and continuous variables, absolute and relative frequency, bar chart, pie chart, histogram; mean, median, mode, range, quartiles, variance, standard deviation, mean-error chart, box diagram). Population, statistical sample.
  2. The basics of probability theory I. The concept of probability, rules of probability calculus.  Probability and odds. Statistical estimation, confidence interval. Odds ratio and 95% confidence interval.
  3. The basics of probability theory II. Conditional probability, 2x2 tables, diagnostic tests, measures of accuracy. The distribution of categorical variables, expected value, and variance.
  4. Notable distributions: the binomial distribution. Continuous distributions: the normal distribution. Standardization, the formula of the binomial test as a special case of standardization.
  5. The central limit theorem, the standard error of the mean. The confidence interval for the population mean. The use of Student’s t-table.
  6. Statistical inference, one-sample t-test. Significance test by a confidence interval, t-statistics, or p-value. The binomial test.
  7. T-tests (one-sample, paired, Student and Welch two-sample t-test )
  8. Statistical errors, one-and two-tailed tests, analysis of variance (principle of one-way ANOVA, F-test, pairwise comparisons).
  9. Correlation-regression analysis. Hypothesis tests for the coefficient of correlation and regression. Regression using transformations.
  10. The chi-squared test for independence (assumptions, Fisher exact test)
  11. Nonparametric methods based on ranks (Wilcoxon-test, Mann-Whitney test, Kruskal-Wallis test, rank correlation)
  12. 2 by 2 tables in epidemiology (measuring agreement using Cohen-Kappa, relative risk, odds ratio)
  13. Survival analysis: life tables, Kaplan-Meier method.


OBLIGATORY TEXTBOOKS

  1. Students can download course material (handouts, lecture notes from the Coospace


SUGGESTED TEXTBOOKS

  1. Michael J. Campell – David Machin – Stephen J. Walters: Medical Statistics. A Textbook for the Health Sciences (2012) ISBN: 978-1-118-30061-9
  2. Internet resources: Khan Academy: https://www.khanacademy.org/math/statistics-probability
  3. Crash Course (Statistics): https://www.youtube.com/playlist?list=PL8dPuuaLjXtNM_Y-bUAhblSAdWRnmBUcr Rice Virtual Lab in Statistics: http://onlinestatbook.com/rvls.html
  4. Reiczigel Jenő – Harnos Andrea – Solymosi Norbert: Biostatisztika nem statisztikusoknak (2014). Pars Kft. ISBN: 978-963-06-3736-7 (In Hungarian)
  5. E-learning (in Hungarian): http://eta.bibl.u-szeged.hu/view/creators/Sz==0171cs=3AM=F3nika=3A=3A.html