Summary
In this chapter we learned how to design the studies while keeping both biological and statistical knowledge. We learned why is biological knowledge important when designing studies in life science areas. We also learned about the Frequentist and Bayesian frameworks in Biostatistics, what are their differences, philosophies and how can they be applied in different Biostatistical analyses and achieve a variety of research goals. We learned about the parameters in biostatistics, their fixed and random variable definitions and how to apply these in research.
Finally, you learned how to connect different experiment and study angles, connect them with the data analysis part and interpret the results of a biological domain studies by integrating the earlier multiple fields mentioned.
In the next chapter, multiple real world exercises including performing PCA (Principal Component Analysis), Latent variable analysis, Structural equation modeling and Bayesian analysis will be...
