Welcome! Today, we're going to explore the stats package available in R, a powerful tool created for advanced statistical computations. One of the major advantages of using a tool like the stats package is its ability to handle complex problems that require multiple calculations — a key feature in areas such as engineering, data science, or any field that heavily relies on data analysis. In this lesson, you'll familiarize yourself with numerous features in the stats package, which will serve as additional tools in your data analytics toolbox.

In statistics, distribution functions play a vital role as they help us identify the probability of potential outcomes for a random event. For example, in a dice game, the distribution function can inform us about the chances of rolling a six. Because we need some data to explore the stats package, let's generate a meaningful data sample using the rnorm() function:

In this example, we generate a vector of 365 values, which are normally distributed with a mean of 30 and a standard deviation of 10.