Quantitative Research: Part 1

Description

The theory of the course 'Research methods and data management: part 1' is aimed at being able to name and describe the different phases in conducting scientific research and the methodological aspects that are important for planning and conducting high-quality research (types of research, study designs, sampling, reliability, validity, principles of measurement, measurement scales, normal distribution, descriptive statistics, statistical inference). The practical sessions focus on applying the theory of the introductory statistical analyses in a standard statistical program. After completing the course, the student can: With regards to research methods: Describe the steps in the research process Name and describe the different types of research (descriptive, exploratory, experimental), with associated designs, questions, hypotheses and frequently used statistical tests Explain the concept of 'sampling' and identify and describe different types of sampling Describe the concepts and types of reliability and validity Name and describe principles of measurement (direct measurements, construct variables) and various measurement scales (nominal, ordinal, interval scale, ratio) Name and describe the characteristics of the normal distribution Know and describe measures of central tendency and variability in descriptive statistics and choose the right descriptive statistical measure for summarizing research data Name and describe the concept of statistical inference and key concepts in inferential statistics (probability, sample errors, hypothesis testing, confidence intervals, type 1 error, type 2 error) With regards to data processing (data management and analysis): Set up a data analysis file in statistical software: data entry, labeling of variables, assigning measurement categories of variables (continuous, nominal, ordinal, interval scale, ratio) Test if continuous variables are normally distributed and interpret and report the output Choose appropriate descriptive statistics for different variables (nominal, ordinal, interval scale, ratio, continuous [measures of central tendency and variability]) and correctly report the output Calculate probabilities in the normal distribution and t-distribution and interpret the output