How do I predict the sales at the mean price level for each brand in this cvs file?
And then how do I model sales as a function of the interaction between price and brand, and the other interaction between price and feature, using log?
This is what I have done for the first part:
x = mean(drinks$price)
print(x)
but I don't understand how I can get the mean price for each individual brand and then predict the sales for each of those brands.
Here is a part of my csv file (called drinks.cvs):
# store week brand sales price feature
1 2 40 tropicana 8256 3.87 0
2 2 46 tropicana 6144 3.87 0
3 2 47 tropicana 3840 3.87 0
4 2 48 tropicana 8000 3.87 0
5 2 50 tropicana 8896 3.87 0
6 2 86 minute.maid 15104 2.09 0
7 2 87 minute.maid 76480 1.39 1
8 2 88 minute.maid 5056 2.39 0
9 2 89 minute.maid 4736 2.39 0
10 2 90 minute.maid 4480 2.39 0
11 2 140 dominicks 4800 2.09 0
12 2 141 dominicks 9664 1.69 0
13 2 142 dominicks 45568 1.69 0
14 2 143 dominicks 20992 1.74 0
15 2 144 dominicks 6592 2.09 0