Answer:
Section a)
Solution;
A correlation coefficient of 0.4 implies a relatively weak positive association between two sets of data. There is a notable small increment in one data set as the other increases.
Section b)
Solution;
A correlation coefficient of -0.96 implies a strong negative association between two sets of data. An increase in the values of one data set amounts to a decrease in the values of the other data set by approximately the same magnitude.
Section c)
Solution;
A correlation coefficient of -0.02 implies a weak negative association between two sets of data. An increase in the values of one data set amounts to a negligible decrease in the values of the other data set.
Section d)
Solution;
A correlation coefficient of 1.0 implies a perfect positive association between two sets of data. An increase in the values of one data set amounts to an increase in the values of the other data set by exactly the same magnitude. A scatter plot would reveal that the line y =x fits the data well.
Section e)
Solution;
A correlation coefficient of 0.86 implies a strong positive association between two sets of data. An increase in the values of one data set amounts to an increase in the values of the other data set by approximately the same magnitude.
Step-by-step explanation:
Correlation coefficient measures the degree of association between two variables or data sets. Correlation coefficients can be positive or negative and may imply weak or strong association between two data sets.
A correlation coefficient of less than 5 is implies a weak association while a value greater than or equal to 5 implies a strong association. Finally, a correlation of 1.0 implies perfect association.
