Predictive Biostatistics Using Python
Most biostatistical studies rely on some form of predictive statistics. The ability to predict an outcome or predict a biological characteristic based on biomarkers is essential in life science. Predictive biostatistics is the key ingredient in many aspects of life science, with areas such as drug discovery and biomedicine being the most relevant examples. In addition to being able to predict outcomes, predictive biostatistics allow researchers to associate risk factors and other biological variables with specific diseases such as diabetes, as well as cardiological and oncology-related diseases.
In this chapter, we’re going to cover the following main topics:
- Learning predictive biostatistics and their uses in different areas of life science
- Understanding dependent and independent variables and their relation to confounders and latent variables
- Implementing linear regression for biostatistics in Python
- Implementing...
