7

4

Here my goal is…

- Find Product 5 (New Product) is really influencing other product sales (product 1 to 4) or not?
- If it is influencing other product sales, how much?

New to R and tried several related posts but didn’t find exact answer to my question. I love R and learning every day something new which helping us in taking data driven decisions.

My sample Dataset is like below (Week and Product 1 to Product 5 Sales per each week) Here my new product is Product 5 and launched on Week 5.

```
Week Product-1 Product-2 Product-3 Product-4 Product-5
1 2 4 5 5
2 4 4 6 4
3 4 4 6 5
4 4 4 6 6 4
5 4 6 5 3 5
6 2 7 6 4 3
7 3 8 7 5 6
8 2 9 9 3 6
```

## Here my questions are

- What is the best process or model to show the influence of product 5 (statistically)?
- Do I need to run co-integration tests before I run correlation? Example some of these products are never be correlated with Product 5 (example: growth in cockle growth vs. growth in electricity demand)
- How I know correlation vs. causation in this mix?
- Since my new product launched on week 5, where I can start my correlations? Is it from week 5 or from earlier weeks?
- Do I need to test for stationarity first? and bring the data to stationary?