The pattern is adding 1.43 to the term before
1.11 + 1.43 = 2.54 + 1.43 = 3.97 + 1.43 = 5.40 . . .and so on.
Answer:
(√2 - √6) / 4
C. square root of two minus square root of six divided by four.
Step-by-step explanation:
sine of negative eleven pi divided by twelve.
We have :
sin(-11π/12)
sin((4 - 15)π / 12) = sin(4π/12 - 15π/12)
sin(4π/12 - 15π/12) = sin(π/3 - 5π/4)
Recall:
Angle difference formula:
sin(A - B) = sinAcosB - sinBcosA
Hence,
sin(π/3 - 5π/4) = sin(π/3) cos(5π/4) − sin(5π/4) cos(π/3)
From trigonometry:
sinπ/3 = √3/2
cos5π/4 = -√2/2
sin5π/4 = -√2/2
cos π/3 = 1/2
(√3/2) (-√2/2) − (-√2/2) (1/2)
-√6/4 - -√2/4
-√6/4 + √2/4
√2/4 - √6/4
(√2 - √6) / 4
Answer:
7/9
Step-by-step explanation:
First distribute -2 to both x and -5
-2(x) = -2x
-2(-5) = 10
2x + 10 = -2x + 10
False. 2x + 10 ≠ -2x + 10
False is your answer
hope this helps
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