Social Medicine and Medical Ethics – Part I Biostatistics Module, Winter Semester 2016/2017
Lecturer: Prof. Rumen Stefanov, PhD
Assistant Professors: Georgi Iskrov, PhD; Ralitsa Raycheva, PhD
Medical University of Plovdiv, Department of Social Medicine and Public Health
Course description: Biostatistics is an introductory course that covers basic statistics concepts and methods used in medicine, public health, and biological sciences. The objectives for this course are for you to be able:
 to understand the importance of collecting data and using appropriate statistical methods in order to test hypotheses and conduct research;
 to recognize the strengths and limitations of basic statistical techniques;
 to conduct analyses using those techniques;
 to better comprehend scientific journal articles containing statistical analyses.
Suggested textbooks: Any biostatistics (medical statistics) textbooks
Course website: Course slides, assignments, data sets, and other relevant materials will be made available on: www.server.raredis.org/edu
Homework: There will be one homework assignment per week, due the following week. Homework should be returned and discussed during the practical classes.
Final exam: There will be a comprehensive final exam of a test, a practical case and a theory question.
Attendance: Regular attendance in this course is mandatory. Homework assignments, tests, and pratical cases will be based entirely on lecture and practical class materials.
Course schedule:
Week 1: Definition of biostatistics. Variables and data. Levels of measurement. Descriptive statistics. Measures of central tendency. Measures of spread. Rule of 3Sigma.
Week 2: Standard error of mean. Confidence Interval for population mean.
Week 3: Standard error of proportion. Confidence Interval for population proportion.
Week 4: Hypothesis testing. Null and alternative hypothesis. Parametric tests. Student ttest for comparing means and proportions.
Week 5: Nonparametric tests. Chisquare test.
Week 6: Correlation analysis. Correlation coefficient. Correlation analysis for quantitative and qualitative variables.
Week 7: Time series analysis.
