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.
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.
Martin is a trained biostatistician, programmer, consultant and data science enthusiast. His main objective: Explaining data science in a straightforward way. You can find his latest work over at: r-tutorials.com
Course Overview [Autogenerated] welcome to exploring data with quantitative techniques using our This is Martin Berger. For pure aside in this intermediate level course, we are step by step exploring a large data set, the data said. Shows flight data off US based airlines, including their delay. Information for each flight in our exploration will focus on the delay data variable spent. How these delays are incurred. Data exploration. It's one of the first things you do when analyzing data. It leads the way to further in depth analysis. It is not always easy to pick the best tools or to decide on a meaningful succession of steps. With this course, I will show you some of the most common than useful tools to explore your data. In the course, you're going to learn about classic summary statistics, which are usually the first thing you do in exploration. Since our data is so large, I will also show you how to use sampling approaches by randomly sampling, A data said you can minimize computation time while still producing valid results, and we're also going to perform several techniques to reveal possible correlations between our variables. To fully benefit from this course, you should have a basic understanding off are a swell a state of exploration. I really hope you're going to use this course to fully develop your data exploration scales in our