Cipher: 1001
Nomenclature: Biostatistics started
Study programme: Molecular biosciences
Module: Compulsory course
Case holder:

The headline izv.prof.dr.sc. Domagoj Šimić, zn.savjetnik-permanent choice
Izv.prof.dr.sc. Andrijana Rebekić
Institution of the case holder:

(DŠ) Agricultural Institute Osijek
(AR) Faculty of Agrobiotechnical Sciences, Josip Juraj Strossmayer University of Osijek
Contributors - Contractors:
Subject status: Compulsory course
The year in which the case is submitted: Year I
The semester in which the case is submitted: Semester I
Subject objective:

To independent students for statistical data processing, interpretation and publication of results within the framework of their own scientific research as well as for successful communication of research results.
Case contents:

Statistical methodology of processing biomedical data in the course of scientific research: types of clinical research, sample and population, data distribution, collection, types and description of data, measurement scales, overview of descriptive statistical indicators (measures of central tendency and dissipation), statistical hypothesis and reasoning, comparison of values between two or more groups, proportions, breakdown of incompletely tracked data and survival curves, sample size, test strength, correlations and regression (multivariate regression, logistical regression and Cox regression test), a breakdown of the characteristics of the receiver's operation. ROC analysis). IT review, display and practice how to use a typical computer program for statistical processing of biomedical data: assigning indicator traits, entering data, storing and transferring data from one form to another. Format printing of processing results, transfer results to tabular or graphical forms of a scientific report.
Learning outcomes: competences, knowledge, skills that the subject develops:

1. Plan statistical processing of data based on objective and hypothesis from your own designed scientific research.
2. Prepare databases and use appropriate computer programs for statistical processing.
3. Interpret data processing reports.
4. Prepare the report for the publication of the results by following the rules of writing the scientific paper.
5. Critically judge the statistical processing of data used in published scientific papers.
ECTS Credits 4
Lectures 5
Seminars (IS) 5
Exercises (E) 30
Altogether 40
The way of teaching and acquiring knowledge:

Regular attendance
Ways of teaching and acquiring knowledge: (notes)

In addition to the introductory lecture and one three-hour seminar, all other classes are done so that each student works on one computer, quite independently, using the program for statistical data processing. All classes happen through problem solving (tasks).
Monitoring and evaluating students (mark in fat printing only relevant categories) Attendance, Teaching activities, Exercise or case study
Rating method: Written exam, Practical work
Mandatory literature:

1. Dawson-Saunders B, Trapp RG. Basic & Clinical Biostatistics. 3rd edition. Prentice-Hall Int. Inc., London, 2000.
2. Petrie A, Sabin C. Medical statistics at a glance. Blackwell Science, Oxford, 2000.
Supplementary (recommended) literature:

1. Petz B. Basic statistical methods for non-athletes. III. Supplemented Exodus Slap Publishing, Jastrebarsko, 1997.
2. Marušić M. Introduction to scientific work in medicine. Rebuilding III. exodus Medical publishing, Zagreb, 2004.
3. StatSoft Inc. Electronic Statistics Textbook. Tulsa, OK: StatSoft, 2002 (http://www.statsoft.com/textbook/stathome.html)
4. Moher D, Schulz KF, Altman DG, for the CONSORT Group. The CONSORT statement: revised recommendations for improving the quality of reports of parallel group randomized trials. Lancet 2001;357:1191-4. (http://www.consort-statement.org/revisedstatement.htm)
How to monitor the quality and performance performance (evaluation):

1. Testing knowledge at the end of each third exercise
2nd test at the end of the survey (anonymous)
3. The success of the course will be evaluated annually by the joint expert committee of the Rudjer Boskovic Institute, the University of Dubrovnik and the University of Josip Juraj Strossmayer in Osijek on the basis of exam successes and surveys.