Introduction to Biostatistics

Description

After completing this course the student will have knowledge of statistics as applied in biomedical research. The student knows the basic concepts of biostatistics (population versus sample, descriptive statistics, p-value and confidence interval, power), and is able to apply these when analyzing data and interpreting the results. The student knows the following statistical techniques and is able to apply and interpret them: comparing paired and unpaired means and proportions, linear regression, ANOVA, logistic regression, Poisson regression, repeated measures analysis, handling missing data and survival analysis. The student also has a basic notion of predictive models, as used in machine learning (a domain within artificial intelligence). The student is aware of methodology used in setting up representative studies (such as population surveys) and comparative studies (such as clinical studies). The student acquires passive and active knowledge in the field of statistical software when applying and interpreting the above techniques.