Answer: THAT IS RIGHT OK BYE MAN
Step-by-step explanation: OK BYE
Answer:
A BT = CT
Step-by-step explanation:
BAT ≅ CAT
That means
The angles are the same and the sides are the same by CPCTC
AB = AC
CT = BT
AT=AT
and
< BAT = <CAT
< ATB = <ATC
< TBA = <TCA
Given the choices on the left
A BT = CT is one of them
- abc + 7abc - 3bc - 8abc
= 6abc - 3bc - 8bc
= -2abs - 3bc
Therefore
- 2abc - 3bc.
:)
1. Introduction. This paper discusses a special form of positive dependence.
Positive dependence may refer to two random variables that have
a positive covariance, but other definitions of positive dependence have
been proposed as well; see [24] for an overview. Random variables X =
(X1, . . . , Xd) are said to be associated if cov{f(X), g(X)} ≥ 0 for any
two non-decreasing functions f and g for which E|f(X)|, E|g(X)|, and
E|f(X)g(X)| all exist [13]. This notion has important applications in probability
theory and statistical physics; see, for example, [28, 29].
However, association may be difficult to verify in a specific context. The
celebrated FKG theorem, formulated by Fortuin, Kasteleyn, and Ginibre in
[14], introduces an alternative notion and establishes that X are associated if
∗
SF was supported in part by an NSERC Discovery Research Grant, KS by grant
#FA9550-12-1-0392 from the U.S. Air Force Office of Scientific Research (AFOSR) and
the Defense Advanced Research Projects Agency (DARPA), CU by the Austrian Science
Fund (FWF) Y 903-N35, and PZ by the European Union Seventh Framework Programme
PIOF-GA-2011-300975.
MSC 2010 subject classifications: Primary 60E15, 62H99; secondary 15B48
Keywords and phrases: Association, concentration graph, conditional Gaussian distribution,
faithfulness, graphical models, log-linear interactions, Markov property, positive
The scale factor is 4 because if you multiply 4 to all the number on figure A it will equal to figure Bs numbers(sorry if it doesn’t makes sense)
