1.8 Chapter 1 Major Takeaways
Any observed data is a sample of a larger population or phenomenon. But you need to consider which population. Is it the population of interest to you? If not, then why?
Sampling strategies impact what type of generalizations we can make about a population. Bias occurs when there are systematic differences between observed sample data and the true population of interest due to the sampling process.
The data we collect many not accurately reflect the truth due to information biases caused by the data collection mechanism (instrument or survey).
Study design impacts what type of conclusions we can make. Confounding variables prevent us from easily making cause and effect conclusions.
We need to be aware of the real and ethical consequences of our choices when working with data and building statistical models.