Answer:
Step-by-step explanation:
1. Find the Greatest Common Factor of the numerator and denominator.
The prime factors of 35 are <u>5</u>, 7, 35
The prime factors of 60 are 2, 3, 4, <u>5</u>, 6, 10, 12, 15, 20, 30, 60
The only common factor of 35 and 60 is 5.
2. Divide the numerator and denominator by the Greatest Common Factor.
Answer:
Jayce should not use either option. Option 1 is likely to be based so that paperbacks are overrepresented, while Option 2 is likely to be biased so that e-books are overrepresented.
Step-by-step explanation:
<em>Given:</em>
<em>Jayce volunteers for the local library. The librarian wants to find out whether the patrons prefer paperback books or e-books. Jayce cannot decide which method to use for polling the patrons.</em>
<em>Option 1: Poll every fifth patron who enters the library on Paperback Lovers Day.</em>
<em>Option 2: Poll every third patron who enters the library on Technology Appreciation Day.</em>
<em />
<em>Since, Option 1: Poll every fifth patron who enters the library on Paperback Lovers Day. It biased because since it paperback lovers day thus, it would be likely that most people like the paperback which make it biased.</em>
<em>Since, Option 2: Poll every third patron who enters the library on Technology Appreciation Day. It biased because since it technology appreciation day thus, it would be likely that most people don't care about these stuff since people coming in are for technology appreciation.</em>
<em />
<em />
<em>Therefore, the answer is:</em>
Jayce should not use either option. Option 1 is likely to be based so that paperbacks are overrepresented, while Option 2 is likely to be biased so that e-books are overrepresented.
<u><em>Kavinsky</em></u>
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:
14.6
Step-by-step explanation:
The area of a rectangle is area=length*width
so we can substitute the numbers here, 262.8=18w
divide 262.8 by 18 to isolate the variable.
You get 14.6.
The width is 14.6.
(x-1)^2+(y-4)=4 is the answer but the pyth theorem is for triangles
