1)
LHS:

LHS = RHS. So, the statement is true
2)
LHS:

LHS not equal to RHS. So, the statement is false
3)
LHS:

LHS = RHS. So, the statement is true.
4)
LHS:

LHS = RHS. So, the statement is true.
Summing all the ingredients to get the total sample size, we applied the formula for obtaining the probability which is
Pr(3) = 0.5
<h3>Probability</h3>
Given Data
Sample Space
Total Sample size = 6
Probability of identifying 3 ingredient used is
Pr(3) = 3/6
Pr(3) = 1/2
Hence the Probability is 0.5
Learn more about probability here:
brainly.com/question/25870256
Answer:
um ight if your asking me if there are right i guess they are...
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