Answer:
Fir trees are 9 meters and the pine trees are 12 meters tall.
Step-by-step explanation:
Let the height of the fir tree = x and the height of the pine tree = y (in meters).
It is given that the combined height of both the trees is 21 meters.
That is, 
Also, the height of 4 fir trees is 24 meters more than that of the pine tree.
That is, 
i.e. 
So, we get the system of equations,
x+y=21
4x-y=24
Adding both the equations, gives us,
5x = 45 i.e. x= 9.
So, x+y=21 ⇒ y= 21 - x ⇒ y= 21 - 9 ⇒ y= 12.
Thus, the fir trees are 9 meters tall and the pine trees are 12 meters tall.
I need $100 for my game console I want. I already have $40 and I get $10 every week for doing chores.
1.6 is let's say one pie and 6/10 of a pie and that's how much a baker made which is obviously more that 1 pie and 3/10 of a pie that the baker made.
A process for that is
1.6 =1 6/10 = 16/10 and if u cross multiply that by
1.3 = 1 3/10= 13/10 the value in the 16/10 side will be 160 which is more that the value on the 13/10 side which is 130
To find the area of the arena, you will need to find the areas of the rectangular spaces and the 2 semicircles. Because the formulas are given, I will just substitute in the values and show the work for finding the areas.
To find the perimeter, you will look at the distances of lines that take you around the space. Because two of these spaces are half circles, you will need to find the circumference of the full circle.
Also, the answers need to be given in meters, so all units given in centimeters will be divided by 100 to convert them to meters.
Perimeter:
C= 3.14 x 20 m
C = 62.8 meters
62.8 + 8 + 25 + 8 + 5 + 8 + 10 + 8 + 40= 174.8 meters for the Perimeter
Area:
A = 25 x 8
A = 200 square meters
A = 10 x 8
A = 80 square meters
A = 20 x 40
A = 800 square meters
A = 3.14 x 10^2
A = 314 square meters
Total Area: 314 + 800 + 80 + 200= 1394 square meters
Given bivariate data, first determine which is the independent variable, x, and which is the dependent variable, y. Enter the data pairs into the regression calculator. Substitute the value for one variable into the equation for the regression line produced by the calculator, and then predict the value of the other variable.
