Association between variables – covariance and correlation

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	115	53	Store17	130	46
Store8	135	47	Store18	115	51
Store9	120	52	Store19	150	41
Store10	155	42	Store20	159	41

 

So far, we have only introduced the basic concepts without elaborating on them practically. It is now time to process the data in the R environment. The first thing to do is load the data...

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