The simplest interpretation would go a little something like this:
We know that we want the total donation amount to be more than $7,900, so we can set up this inequality to begin with

Where
D is the total donations raised (in dollars). How do we find D? Well, we just add up the total number of table reservations sold and the total number of single tickets sold. If we let
r stand for the number of reservation tickets and
s stand for the number of single tickets, then we have

So, the inequality representing this situation would be

And that would probably be fine for this problem.
<span><em>Footnote:</em>
</span>Of course, if this were a real-life scenario, we'd need to take some additional details into account: How many tables do we have? How many people can be seated at each table?
Answer:
- Right Angle Triangle – A Right triangle is a triangle in which one angle is a right angle (that is, a 90-degree angle). The relation between the sides and angles of a right triangle is the basis for trigonometry (opposite, hypotenuse, adjacent).
- Obtuse Triangle – An obtuse triangle is a triangle with one obtuse angle (greater than 90°) and two acute angles.
- Acute Triangle – An acute triangle is a triangle with three acute angles (less than 90°).
12 - Right Angle Triangle
13 - Obtuse Triangle
14 - Acute Triangle
15 - Acute Triangle
16 - Right Angle Triangle
17 - Obtuse Triangle
7x - 5y = 21....(4,?)...so sub in 4 for x and solve for y
7(4) - 5y = 21
28 - 5y = 21
-5y = 21 - 28
-5y = - 7
y = 7/5
check..
7(4) - 5(7/5) = 21
28 - 35/5 = 21
28 - 7 = 21
21 = 21 (correct)
the other coordinate is 7/5......(4,7/5)
There is an association because the value 0.15 is not similar to the value 0.55
For the nutritionist to determine whether there is an association between where food is prepared and the number of calories the food contains, there must be an association between two categorical variables.
The conditions that satisfy whether there exists an association between conditional relative frequencies are:
1. When there is a bigger difference in the conditional relative frequencies, the stronger the association between the variables.
2. When the conditional relative frequencies are nearly equal for all categories, there may be no association between the variables.
For the given conditional relative frequency, we can see that there exists a significant difference between the columns of the table in the picture because 0.15 is significantly different from 0.55 and 0.85 is significantly different from 0.45
We can conclude that there is an association because the value 0.15 is not similar to the value 0.55
I’m sorry, but how do I see you’re recent questions? I’d love to help! However I have no clue how to find the questions.