First, we calculate x*y, x*x and y*y for each pair (xi, yi) and fill out the three last column of the table about. Second, the total for each column is found. Now we have all the numbers necessary to determine the correlation coefficient:
The correlation coefficient of 0.813 indicates a strong positive between linear relationship retail online sales and total retail sales variables (X and Y)…
For example, correlation between the advertising expenditures or promotional activities in certain area and the total sales in the corresponding period in that area is of interest for the managers. They want to determine how effective is the advertising/promotion and forecast the sales given increase or decrease in advertising.
However, the correlation values should be treated carefully. It characterizes the strength of the linear relationship; therefore, if the relationship between two given variables is quadratic, logarithmic or exponential, then the correlation coefficient will not adequately reflect how strong the relationship is. Moreover, even the relationship between variables is linear, high positive value of the coefficient does not indicate which of the variables causes the change in the value of another. The situation when both of them are influenced by the third variable and change simultaneously is also possible.
In a business context, a lot of attention should be paid to the economic relationship between variables. ...
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