6!+7!+8!=(n)(6!)
calculate the individual values first:
6!=720
7!=5040
8!=40320
plug them into the equation:
720+5040+40320=n720
solve for n
5760+40320=n720
46080=n720
divide both sides by 720 to isolate n
46080/720=n720/720
64=n
Step-by-step explanation:
6. 7x + 7y = -11
7. -1x + 8y = 12
8. 9x + 11y = -7
Step-by-step explanation:
this sequence is geometric not arithmetic
HOw we know that ??
when we get a common difference that must Be equal
d=6-2=4 not equal to d=18-6=12
So it is not arithmetic
but when we get the common ratio that also must be equal
r=6/2=18/6=54/18=3 equal
So it is geometric
By using this equation:
a(n)=a(1)*r^(n-1)
and we have a(1)=2 , r=3
<u>Explicit rule:</u> a(n)=2*(3)^(n-1)
<u>Recursive rule:</u> a(n)= r * a(n-1)
a(n-1) ⇒ priviuse term
SO: a(n)= 3 * a(n-1)
For example:
a(3)= 3 * 6 =18
<em>I really hope this helps <3</em>
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
Answer:
The equation would be y = -2x + 1
Step-by-step explanation:
All you have to do is put it in the form y = mx + b where m is the slope and b is the y-intercept (for example, the equation y= 2x + 1 has a slope of 2 and a y-intercept of 1.)
Since you have slope, or m, = -2 and the y-intercept, or b, = 1, the equation would be y = -2x + 1
