Imagine that a researcher correctly computes a correlation coefficient to quantify the relationship between two variables. In the data set that she works with, low scores on Variable X tend to be paired with low scores on Variable Y, and high scores on Variable X tend to be paired with high scores on Variable Y. Based on this data set, what type of correlation coefficient should the researcher expect to find

Positive value of correlation Coefficient

Step-by-step explanation:

The correlation Coefficient value, R is a correlation measure which gives information about both the strength of association between two variables and also the type of association between them (negative or positive). R has a standardized value which ranges from - 1 to +1

Negative relationship between variables are depicted with negative (where one variable decreases as the other increases) R value while positive association (increase in one variable means leads to increase in the other variable) are depicted with positive R values.

Therefore, for the relationship described above, the correlation Coefficient will be positive.

last one.

step-by-step explanation:

last one.

generally speaking, the others follow some sort of pattern that correlates to either linear (looks like a straight line) or sinusoidal (looks like an s).

the last one is just a random cloud of points that doesn't correlate to any particular known order.

the answer is b.

step-by-step explanation:

identity property is where 0+whatever number=whatever number. basically 0+ a number.