Answer:the repair shop is 5km from her house.
Step-by-step explanation:
Let x represent the distance of the repair shop from her house.
Let y represent Emily's speed when riding.
Distance = speed × time
It took Emily 25 min to ride her bike to the repair shop. Converting 25 min to hours, it becomes 25/60 = 5/12 hours.
Distance covered,
x = y × 5/12 = 5y/12
It took her 1h 15 min to walk back home. Converting to hours, it becomes 1 + 15/60 = 1 1/4 = 5/4
If she can ride her bike 8km/h faster than she can walk, it means that her speed while walking would be y 8 8
Therefore,
Distance covered,
x= 5/4(y - 8) = (5y - 40)/4
Since the distance remains the same, then
5y/12 =(5y - 40)/4
Crossmultiplying, it becomes
5y × 4 = 12(5y - 40)
20y = 60y - 480
60y - 20y = 480
40y = 480
y = 480/40 = 12
x = 5y/12 = 5 × 12/12 = 5 km
Answer:
-12.133 would be your answer
Answer:
D) v = -2,000y + 20,000.
Step-by-step explanation:
The question gives a linear relationship between two quantities. This means that the relationship between the initial value of the car and the amount it depreciates each year is proportional, or constant. Since the value of the car decreases by 10% of its initial value each year, then each year the value will decrease by 10% of 20,000 or 0.10 x 20000 = $2,000. Since we know the value is decreasing each year, this amount would be subtracted from the initial value of $20,000. So, D) v = -2,000y + 20,000 would be the only equation that represents this scenario.
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:
Apparently i cant see the photo im am so sorry but do need pints.
Step-by-step explanation:
