AbstractThis chapter explores the fluctuations of random variables away from their mean value. You flip a fair coin 100 times. How likely is it that you get 60 heads? Conversely, if you get 60 heads, how likely is it that the coin is fair? Such questions are fundamental in extracting information from data.In Sect. 3.1, we start by exploring the rate available to a user when a random number of them share a link, as illustrated in Sect. 3.1. Such calculations are central to network provisioning. The main analytical tool is the Central Limit Theorem explained in Sect. 3.2 where Gaussian random variables are also introduced and confidence intervals are defined. To share a common link, devices may be attached to a switch. For instance, the desktop computers in a building are typically connected to a switch that then sends the data to a common high-speed link. We explore the delays that packets face through the buffer of a switch in Sect. 3.3. The analysis uses a Markov chain model of the buffer. To share a wireless radio channel, devices use a multiple access protocol that regulates the transmissions. We study such schemes in Sect. 3.4. We use probabilistic models of the protocols.