Interpreting Data Using Statistical Models in R

by Fredrik Hallgren

This course introduces the most important methods and concepts from statistics with applications in the R programming language. We cover the fitting of statistical models to data, statistical testing, and prediction.

What you'll learn

We need principles, models, and theory to make sense of the vast amounts of data generated in today’s world. In this course, Interpreting Data Using Statistical Models in R, you will gain the ability to apply statistical and data science models to any task. First, you will learn how to fit statistical models to data. Next, you will discover how to test for relationships in data. Finally, you will explore how to create predictions with linear regression. When you are finished with this course, you will have the skills needed to turn data into knowledge.

About the author

Fred Hallgren is a PhD candidate in machine learning at University College London (UCL). His interest for technical teaching was sparked as a teaching assistant in mathematics while an undergraduate and during his PhD he has taught extensively in statistics and statistical programming to undergraduate and masters students. His research at UCL has focused on kernel methods, neural networks and dimensionality reduction. Prior to his PhD he worked at a quantitative hedge fund, researching trading m... more

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