Instead of trusting gut feeling and guesses, data scientists trust data. Descriptive statistics are wonderful for introducing data and scavenging for insights. Statistical hypothesis testing is a great way to check how likely some behavior displayed by data is due to an actual trend or randomness. Although some key statistical concepts are recovered during the chapter, readers will greatly benefit from prior knowledge on probabilities and distributions. This chapter will discuss how to use R to draw descriptive analysis and test hypothesis.

The following topics are discussed in this chapter:

• Most commonly used descriptive measures
• How to summarize data with little effort
• How to set up a t-test
• How to design a function to run z-tests
• How to store and get your functions from the cloud
• How to use Fisher's exact test to run an A/B test