Probability theory is the branch of mathematics concerned with probability, the analysis of random phenomena. The central objects of probability theory are random variables, stochastic processes, and events: mathematical abstractions of non-deterministic events or measured quantities that may either be single occurrences or evolve over time in an apparently random fashion.

Descriptive statistics are statistics that quantitatively describe or summarise features of a collection of information.[1] Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent.

A computer is a tool for solving problems with data.

A program is a sequence of instructions that tell a computer how to do a task. When a computer follows the instructions in a program, we say it executes the program. You can think of it like a recipe that tells you how to make a peanut butter sandwich. In this model, you are the computer, making a sandwich is the task, and the recipe is the program that tells you how to execute the task.

Digital electronics or digital (electronic) circuits are electronics that handle digital signals – discrete bands of analog levels – rather than by continuous ranges as used in analog electronics. All levels within a band of values represent the same information state. Because of this discretization, relatively small changes to the analog signal levels due to manufacturing tolerance, signal attenuation or noise do not leave the discrete envelope, and as a result are ignored by signal state sensing circuitry.

Computer science studies how to describe, predict properties of, and efficiently implement information processes. This book introduces the most important ideas in computing using the Scheme and Python programming languages.

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