In the lecture titled “Bias in Clinical/Translational Research,” the speaker explores the factors that introduce bias, affecting the accuracy and significance of clinical investigations. The lecture delves into the various sources of bias that can manifest at the inception of a study, during participant selection, data collection, and in the interpretation and reporting of data. The discussion encompasses issues such as information bias, measurement errors, selection bias, identification of confounding variables, and the implementation of quality assurance techniques to enable researchers to validate data and account for errors.
In the lecture “Analyzing Data and Interpreting the Results,” the presenter goes a step further to elucidate the data analysis process in the realm of biomedical research. This process involves the formulation of a research question, hypothesis development, and the design of a study. The lecture offers insights into best practices for coding and presenting data, creating statistical summaries, employing various chart types, and using other methods for data visualization. The lecture also covers hypothesis testing and the synthesis of results to provide a comprehensive understanding of data analysis in biomedical research.