Focus will be on standard descriptive methods and parametric statistical models, especially analysis of variance and regression models, as well as more advanced methods including models for repeated measurements; a frequentist point of view will mostly be adopted. It will be a modern approach towards the use of statistical methods, reflecting current practice in nutritional and physiology research as seen in the research activities at NEXS w.r.t. publication of scientific articles and reports. Choice of appropriate statistical models will be a key theme, i.e., how to translate study designs into suitable parametric model specifications, both for randomized controllled trials (e.g., parallel-arm and cross-over trials) and for observational studies (e.g., cohort and cross-sectional studies). Estimation of relevant parameters such as means, differences, and slope coefficients will be of particular relevance. Moreover, methods for improved efficiency and for reducing bias such as relevant adjustments for covariates and confounders  will also be covered. Assessment of uncertainty of estimates by means of confidence intervals and standard errors will also be an integral part of the course; p-values will also be discussed. Statistical methods will mainly be introduced and discussed through reading of selected parts of publications and other relevant literature. The first 6 weeks of the course will consist of lectures and exercises. The last two weeks will consist of project work where participants will reanalyze publicly available data, using the knowledge and skills they acquired during the first 6 weeks. The statistical environment R will be used throughout the course.