In the previous chapter, we introduced correlation concepts, and it is now necessary to deepen these concepts. This will help us understand how to use this information in advance and find possible relationships between variables. Let's start with a real example: a company at the launch of a new printer model wants to analyze sales at a number of stores to determine the best price. The following table shows the sales of the product in the last month and the sale price for these stores:
Store |
SoldItems |
Price |
Store |
SoldItems |
Price |
Store1 |
100 |
60 |
Store11 |
145 |
42 |
Store2 |
150 |
43 |
Store12 |
125 |
47 |
Store3 |
130 |
48 |
Store13 |
135 |
44 |
Store4 |
140 |
45 |
Store14 |
105 |
54 |
Store5 |
110 |
55 |
Store15 |
155 |
39 |
Store6 |
160 |
40 |
Store16 |
110 |
52 |
Store7 | ...