Answer:
0.166
Step-by-step explanation:
We know that,
1 week = 7 days
i.e.
6 week = 7(6) days = 42 days
We need to express ratio 7 days to 6 weeks as a decimal fraction. So,

Qué es?
<span> <span>A.</span>Es una grapadora.</span><span> <span>B.</span>Es una puerta.</span><span> <span>C.</span>Es un mapa.</span><span> <span>D.</span><span>Es un cartel.</span></span>
Let
be the dimensions of the rectangle. We know the equations for both area and perimeter:


So, we have the following system:

From the second equation, we can deduce

Plug this in the first equation to get

Refactor as

And solve with the usual quadratic formula to get

Both solutions are feasible, because they're both positive.
If we chose the positive solution, we have

If we choose the negative solution, we have

So, we're just swapping the role of
and
. The two dimensions of the rectangle are
and 
There could be a strong correlation between the proximity of the holiday season and the number of people who buy in the shopping centers.
It is known that when there are vacations people tend to frequent shopping centers more often than when they are busy with work or school.
Therefore, the proximity in the holiday season is related to the increase in the number of people who buy in the shopping centers.
This means that there is a strong correlation between both variables, since when one increases the other also does. This type of correlation is called positive. When, on the contrary, the increase of one variable causes the decrease of another variable, it is said that there is a negative correlation.
There are several coefficients that measure the degree of correlation (strong or weak), adapted to the nature of the data. The best known is the 'r' coefficient of Pearson correlation
A correlation is strong when the change in a variable x produces a significant change in a variable 'y'. In this case, the correlation coefficient r approaches | 1 |.
When the correlation between two variables is weak, the change of one causes a very slight and difficult to perceive change in the other variable. In this case, the correlation coefficient approaches zero