Statistics plays a foundational role in data science and applied mathematics. In addition to the theory, we must understand the role of statistics and probability in practice and be able to connect it to real world applications. This is most often seen through the use of probability distribution/mass functions that allocate probability to events of interest. However, sample size, sampling mechanisms and other factors can and do have an impact on the data we collect in practice. In this short course, we will use R to learn about statistical theory as well as simulate data from a variety of distributions and models, e.g., linear models, generalized linear models, and hierarchical models.
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