Exploring Data with Quantitative Techniques Using R

by Martin Burger

Data exploration is one of the first things you do when analyzing data. It leads the way to further in depth analysis. With this course, you will learn how to use R for data exploration of a large dataset.

What you'll learn

Do you want to perform data exploration on a large dataset? In this course, Exploring Data with Quantitative Techniques Using R, you will see why R is a great tool in getting to know your data. The course uses a 3 step approach to explore the NYC flights dataset. First, you will get an initial idea via summary statistics. Then, you will use hypothesis tests and visualizations to work on single variables. Finally, you will use techniques for correlations between multiple variables. On top of that, the course also has a module on data sampling which is especially useful for large datasets. When you are finished with this course, you will have the skills and knowledge of data exploration needed to understand a new dataset. You will also use some outstanding add-on packages for the topic.

About the author

Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.

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