<span>y=+- square root 5 over 3
y^2 + x^2 = 1 => x^2 = 1 - y^2 = 1 - 5/9 = 4/9 => x = +/- 2/3
Answer: x = +/- 2/3
y=+- square root 7 over 3
y^2 + x^2 = 1 => x^2 = 1 - y^2 = 1 - 7/9 = 2/9 => x = +/- (√2) / 3
Answer: x = +/-(√2)/3
y=+- 3 over 3
x^2 = 1 - y^2 = 1 - 3/9 = 1 - 1/3 = 2/3 => x = +/-(√2/3)
Answer: x = +/-√(2/3)
y=+- 2 square root 2 over 2
= y = +/- 2(√2) /2 = √2 ...... these y-coordinates are out of the unit circle, then there is not a corresponding x - coordinate for them.
</span>
Her school is 2/3 miles away
2/3=4/6miles
So we need to find out how long it will take for her to run home from school...
School=4/6 miles
In 1 minutes she can run 1/6 miles
1min=1/6miles
In 2 minutes she can run 1/6+1/6 miles (1/6+1/6=2/6)
2min=2/6miles
3min=3/6miles
4min=4/6miles
It will take Erica 4 minutes to run 4/6 miles, so it'll take her 4 minutes to get home.
Remember
xyz=(x)(y)(z)
if x and y and z are all perfect cubes, xyz is also a perfect cube
remmeber
(x^n)^m=x^(mn)
so if it is perfect cube it can be factored into
(x^n)^3, such taht n is a whole number
basiclaly, see if the expoent is divisble by 3
all of them should be perfect cubes
215x^18y^3z^21
split them up to see which ones need changing
215=5*43, not a perfect cube
could be changed to 6^3, which is 216
x^18=(x^6)^3
y^3=y^3
z^21=(z^7)^3
the 215 needs to be changed
Answer:
The correlation coeffcient for this case was provided:
r =0.934
And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .
We can also find the
who represent the determination coefficient and we got:

And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables
Step-by-step explanation:
Previous concepts
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
And in order to calculate the correlation coefficient we can use this formula:
The correlation coeffcient for this case was provided:
r =0.934
And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .
We can also find the
who represent the determination coefficient and we got:

And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables