The answer is the first one
Answer: A
Step-by-step explanation:
The nominal scale by definition only deals with non-numeric or non-quantitative variables or where numbers have no numerical value. The nominal scale uses tags or labels instead of number to classify or identify an object being measured.
Big rectangle
3x-4 (2x+2) = 6x^2-8x+6x-8
=6x^2-2x-8 = 3x^2-x-4
Small rectangle
(X-3) (x-6) = x^2-3x-6x+18
=x^2-9x+18
Big-small= 2x^2+8x-22 is the area of the shaded region
11,15,19,23
an = 11 + 4(n-1)
an = 11 + 4n - 4
an = 4n + 7
R = 0.9
A value of 0.9 would indicate that the correlation is positive. Since it's also close to the value 1, it would also tell us that the correlation of y and x is strong. Therefore, r = 0.9 would be a strong linear association in which y increases as x increases.
r = -1.0
Since the value of r is negative, this would mean that the correlation is also negative. Furthermore, the value of r is also at the minimum point which is -1.0 thus this would tell us that the correlation is a perfect linear association in which y decreases as x increases.
r = -0.6
Likewise, this r value is also negative thus allowing us to know that y will decrease as x increases. The value of r, which is -0.6, is also close to -1.0. This allows us to tell that it is a strong relationship. Therefore, r = -0.6 is a strong linear association in which y decreases as x increases.
r = 0.1
For this correlation, the r value is positive. This would indicate that the value of y will increase as x increases. Since the r value is only 0.1, we cannot say that it is a strong relationship since it is far from the maximum value for a perfect relationship which is 1. Therefore, r = 0.1 is a moderate linear association in which y increases as x increases.
