Statistics Part 1: Theory and Exercises

Description

This course contributes to the following learning outcomes of the course - Can collect, use and interpret health data correctly - Can identify and critically evaluate the validity of scientific evidence - Can understand and apply various methods of data collection within a qualitative and / or quantitative research design, analyze data and interpret them critically The following learning objectives apply at the end of this course - Know the rules of empirical research and the hypothetical-deductive model, as well as the difference between exploratory and inferential research - Know the techniques of descriptive statistics and their application and interpretation - Know the difference between population and sample - Know the concepts of correlation and causality and the difference between them - Know the concepts of frequency and probability distribution and the difference between them - Know the general principles of inferential statistics, the concepts p-value and confidence interval and know how to apply these techniques and interpret them. - Know the methodology of hypotheses testing and the concepts of type I and type II errors and know how to apply these techniques and interpret them. - Know parametric and non - parametric techniques to analyze independent or unpaired samples and dependent or paired samples. - Know different measures of association for continuous variables and the corresponding inferential procedures and know how to apply these techniques and interpret them. - Know simple linear regression models, and the corresponding inferential procedures and know how to apply these techniques and interpret them