Answer:
You will graph a function with the equation being y = 4x - 3, to plot this function read step by step explanation.
Step-by-step explanation:
First we have to find the equation of the line so we do....
24x - 6y = 18
24x = 18 + 6y
6y = 24x - 18
y = 4x - 3
Now that we know the equation we just have to find two point by using this equation and connect them between each other in order to graph the function represented by this equation. For example
For x = 0
y = 4x - 3
y = -3
So we know that there is a point (0, - 3)
For x = 1
y = 4x - 3
y = 4 - 3
y = 1
So we know that there is a a point (1, 1)
Connect the two point and you will get the function graph
Could depend on many things, but i believe it would be ounce.
Hey there! I'm happy to help!
The Greatest Common Factor is self-explanatory: it is the largest factor that both numbers have in common. Let's look at the factors of each of these numbers:
30: 1, 30, 2, 15, 3, 10, 5, 6
45: 1, 45, 3, 15, 5, 9
We see that the largest number they both have in common is 15, so the GCF is 15.
Have a wonderful day! :D
Answer:
Kindly check explanation
Step-by-step explanation:
Given that :
Correlation Coefficient (r) = 0.989
alph=0.05
Number of observations (n) = 8
determine if there is a linear correlation between chest size and weight.
Yes, there exists a linear relationship between chest size and weight as the value of the correlation Coefficient exceeds the critical value.
What proportion of the variation in weight can be explained by the linear relationship between weight and chest size?
To determine the the proportion of variation in weight that can be explained by the linear regression line between weight and chest size, we need to obtain the Coefficient of determination(r^2) of the model.
r^2 = square of the correlation Coefficient
r^2 = 0.989^2 = 0.978121
Hence, about 0.978 (97.8%) of the variation in weight can be explained by the linear relationship between weight and chest size.
