The modern data analyst is no longer adequately served by spreadsheet-type software and off-the-shelf one-size-fits-all software solutions. Companies are looking for multi-skilled individuals who can:
- translate business challenges into discrete solvable problems,
- operationalize these problems into testable hypotheses,
- apply appropriate statistical methods to data to rigorously test these hypotheses,
- and derive actionable business strategy and inform decision making.
This class focuses on solving problems with a computational applied approach and as such a basic background in statistics is essential. We will explore the description and visualization of data, designing and performing experiments; creating statistical models based on domain knowledge; testing our understanding against data; and generating appropriate conclusions. We will learn a wide range of essential statistical methods and gain hands-on experience using different statistical techniques and tools.Requirements:
Basic knowledge of undergraduate statistics is advised.Completion of SWIRL R tutorial is strongly advised: https://swirlstats.com/