Answer:
B - Strong Negative
Explanation:
In scientific research, correlation coefficients are very important to draw panoramas in studies with many related variables, because it is possible to understand how the variability of one affects the other. Pearson's correlation coefficient (r), also called Pearson's linear correlation or r, is the most famous and common coefficient of correlation, it is a degree of relationship between two quantitative variables and expresses the degree of correlation through values between -1 and 1.
When the correlation coefficient approaches 1, there is an increase in the value of one variable when the other also increases, that is, there is a positive linear relationship. When the coefficient approaches -1, it is also possible to say that the variables are correlated, but in this case when the value of one variable increases that of the other decreases. This is what is called negative or inverse correlation.
A correlation coefficient close to zero indicates that there is no relationship between the two variables, and the closer they come to 1 or -1, the stronger the relationship.
