The Beta distribution is a continuous probability distribution defined on the interval \([0, 1]\). It is often used to model random variables that represent probabilities or proportions. The distribution is parameterized by two positive shape parameters, denoted as \(\alpha\) and \(\beta\), which influence the shape of the distribution.
Bernoulli's triangle is a mathematical construct related to the binomial coefficients, similar to Pascal's triangle. The elements of Bernoulli's triangle are known as Bernoulli numbers, which are a sequence of rational numbers that have important applications in number theory, analysis, and combinatorics.
The Turán number, denoted as \( T(n, r) \), is a concept in combinatorial mathematics, specifically in the field of graph theory. It represents the maximum number of edges in a graph with \( n \) vertices that does not contain any complete subgraph (or clique) with \( r \) vertices. In other words, it provides an upper limit on the edge count of a graph while avoiding certain cliques.
The Turán graph, denoted as \( T(n, r) \), is a specific type of graph used in extremal graph theory, which studies the conditions under which graphs contain certain subgraphs. The Turán graph is designed to be the largest \( K_{r+1} \)-free graph (a graph that does not contain a complete subgraph of \( r+1 \) vertices) with \( n \) vertices.
Homomorphism density is a concept from combinatorics and graph theory that deals with the frequency of the occurrence of one graph within another graph. More formally, it relates to the density of homomorphisms from one graph to another.
The Forbidden Subgraph Problem is a concept from graph theory, related to understanding the structure of graphs by identifying certain subgraphs that are "forbidden" or not allowed within a graph. More formally, the problem can be described as follows: Given a graph \( G \) and a set of graphs \( H \), the Forbidden Subgraph Problem asks whether \( G \) contains any subgraph that is isomorphic to any of the graphs in the set \( H \).
Dependent random choice is a concept mainly used in probability theory and stochastic processes. It refers to a selection process where the choices made are not independent of one another; rather, the outcome of one choice influences the probabilities of subsequent choices. In a typical independent random choice scenario, the probability of each outcome remains constant regardless of what has happened before. However, in dependent random choice, the selection of one item or event alters the likelihood of selecting other items or events in the future.
In the context of computer science and mathematics, a "common graph" can refer to different concepts depending on the specific area of discussion. However, it is not a universally defined or standard term.
A **biclique-free graph** is a graph that does not contain any complete bipartite subgraph \( K_{m,n} \) as a subgraph. A complete bipartite graph \( K_{m,n} \) consists of two disjoint sets of vertices \( U \) and \( V \) where every vertex in \( U \) is connected to every vertex in \( V \), and there are no edges between vertices within the same set.
A rotation map is a function that describes the process of rotating points or vectors in a mathematical space, typically in two or three dimensions. In 2D space, for example, a rotation map takes a point represented by coordinates \((x, y)\) and rotates it by a certain angle \(\theta\) around the origin.
A rooted graph is a type of graph in which one particular vertex is designated as the "root." This root serves as a reference point for various operations and representations associated with the graph. Rooted graphs are commonly used in various areas of computer science and mathematics, especially in the context of tree structures, where the graph is typically acyclic and hierarchical. Key characteristics of a rooted graph include: 1. **Root Vertex**: One vertex is distinguished as the root.
A quantum graph is a mathematical structure that combines concepts from quantum mechanics and graph theory. Specifically, it consists of a graph in which the edges are treated as one-dimensional quantum wires and the vertices represent potential interaction points. The study of quantum graphs involves analyzing the behavior of quantum particles, such as electrons, as they move along the edges and interact at the vertices.
An ordered graph is a type of graph in which the vertices and edges are organized in a specific sequence. This ordering can be applied in various ways depending on the context and the specific properties being examined. Here are a few interpretations of "ordered graph": 1. **Directed Graphs**: In directed graphs (or digraphs), the edges have a direction, meaning that they go from one vertex to another. The order of vertices and the direction of edges can be seen as a specific arrangement.
A **multigraph** is a type of graph in graph theory that allows for multiple edges between the same pair of vertices. This means that in a multigraph, it is possible to have two or more edges connecting the same vertices (like A and B) in addition to the regular edges that connect different pairs of vertices. In contrast, a simple graph does not allow multiple edges between the same pair of vertices or self-loops (edges that connect a vertex to itself).
Graph labeling is a process used in graph theory where labels (which can be numbers, symbols, or other identifiers) are assigned to the vertices or edges of a graph according to specific rules or constraints. The purpose of graph labeling can vary and may include optimizing certain properties of the graph, creating unique identifiers for the elements, or ensuring that the graph meets particular criteria for applications in areas such as network design, scheduling, or coding theory.
A **bidirected graph** (also known as a bidirectional graph) is a type of graph in which edges have a direction that allows for travel in both directions between any two connected vertices. In other words, if there is an edge from vertex \( A \) to vertex \( B \), it can also be traversed from vertex \( B \) back to vertex \( A \).
An ancestral graph is a concept used mainly in the context of statistics and genetics to represent relationships among a set of variables or individuals, particularly in the study of evolutionary biology. Ancestral graphs can be characterized as directed acyclic graphs (DAGs) that capture the causal relationships and ancestral lineage among the variables. In an ancestral graph: 1. **Nodes** represent variables or individuals. 2. **Directed edges** indicate directionality, showing ancestral relationships (e.g.

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 5. . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact