The data set Direct Mail.xls contains data on direct mail campaign conducted by an antique dealer. It is a weekly time-series data with two variables sales (in thousands) and direct mail which is the direct mail costs (in dollars). 1. Get the summary statistics for both variables and comment on them. 2. Create time-series plot of sales by week. 3. Comment on the trend you see on the chart. 4. Create a scatter diagram using Sales as the response variable and Direct Mail as the predictor variable? Ae the variables related to each other? 5. Determine the correlation between the variables and comment on the nature and strength of relationship between them. 6. Use simple linear regression technique to identify the cause-and-effect relationship between Sales and Direct Mail. 7. Comment on the goodness of fit of the regression equation for the data. Do you think your prediction is accurate?

Week	Sales	Direct Mail
1	12.123	98
2	21.209	212
3	9.998	561
4	42.978	413
5	49.637	267
6	31.645	321
7	28.698	529
8	49.611	731
9	38.908	695
10	78.735	544
11	44.631	87
12	38.941	299
13	42.004	243
14	62.938	423
15	41.937	820
16	74.007	602
17	49.873	489
18	62.178	279
19	31.762	376