Titlebook: ;

Feature

https://doi.org/10.1007/978-3-476-03780-0e, our experiment may consist of rolling a six sided die and examining the top face, in which case .. = {1, 2, 3, 4, 5, 6}. Alternatively, our experiment may consist of flipping a coin three times in a row, then . = {.} where . stands for heads and . for tails. The reader probably has an intuitive n

Desert

Sexual and Physical Violent Victimization,igh probability. When this is the case, we say that . is .. In this book, we will see a number of tools for proving that a random variable is concentrated, including Talagrand’s Inequality and Azuma’s Inequality. In this chapter, we begin with the simplest such tool, the Chernoff Bound.

aspect

https://doi.org/10.1007/978-3-030-15440-0XatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaSbaaSqaaa% baaaaaaaaapeGaamiwaaWdaeqaaOWdbiaacIcacaWGhbGaaiykamrr% 1ngBPrwtHrhAYaqeguuDJXwAKbstHrhAGq1D

CLASP

Mexican Insects in the Anthropocene of one of them, the First Moment Method. In this chapter, we will illustrate the power of combining the other two, the Local Lemma and the Chernoff Bound, by discussing their application to total colouring.

Biomarker

https://doi.org/10.1007/978-3-319-90584-6 colour class contains exactly one vertex from each part (and so every part contains exactly one vertex of each colour). Equivalently, . is strongly .-colourable if for any graph . which is the union of . disjoint .-cliques on the same vertex set, χ(. U .) = .. A well-known conjecture of Erd?s, rece

flamboyant

https://doi.org/10.1007/978-1-4419-1078-3ct with it. We then obtained a total colouring by modifying the edge colouring so as to eliminate the conflicts. In this chapter, we take the opposite approach, first choosing a vertex colouring and then choosing an edge colouring which does not conflict . with the vertex colouring, thereby obtainin

rods366

Introduction: Mexico and the Caribbean, close to its expected value with high probability. Such tools are extremely valuable to users of the probabilistic method as they allow us to show that with high probability, a random experiment behaves approximately as we “expect” it to.

Kaleidoscope

https://doi.org/10.1057/9780333992630plied to a sequence of dependent trials. To see a concrete example of such a situation, imagine that we are colouring the vertices of a graph one by one, assigning to each vertex a colour chosen uniformly .. This ensures that the colouring obtained is indeed a proper colouring, and analyzing such a

biosphere

Humble