Answer:
Step-by-step explanation:
x/4-y/2=8, x-2y=32, x=32+2y
x/2+3y/4=-5, 2x+3y=-20, x=(-20-3y)/2
32+2y=(-20-3y)/2
64+4y=-20-3y
7y=-84
y=-12, since x=32+2y
x=32+2(-12), x=32-24=8
So the solution is the point (8, -12)
Answer:
h = 4x ^ 3 + 18
Step-by-step explanation:
The first thing you should know for this case is that the area of a triangle is given by:
A = (1/2) * (b) * (h)
Where,
b: base.
h: height.
Clearing the height we have:
h = ((2) * (A)) / (b)
Substituting the values
h = ((2) * (14x ^ 5 + 63x ^ 2)) / (7x ^ 2)
Simplifying the expression:
h = ((2) * (2x ^ 3 + 9))
h = 4x ^ 3 + 18
answer
an expression to represent its height is
h = 4x ^ 3 + 18
Yes, it’s option one where y is neg five
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
