Answer:
the answer to this equation is 23
Answer:
Your answer would be D!
Step-by-step explanation:
Answer: Simple and best practice solution for 4y^2+8y+1=0 equation. ... Begin completing the square. ... Square it (1) and add it to both sides.
Step-by-step explanation: Complete the square for x2+2x x 2 + 2 x.
The side lengths of the mirrors are 1.5 ft and 2.5 ft respectively.
<u><em>Explanation</em></u>
Given that, the area of smaller mirror is 2.25 ft² and the area of larger mirror is 6.25 ft²
<u>Formula for the area of a square</u> : 
, where 
is the side of the square.
Lets assume, the side length of smaller mirror is 
ft and the side length of larger mirror is 
ft.
So....
and
Thus, the side length of smaller mirror is 1.5 ft and side length of larger mirror is 2.5 ft.
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
