Timeline for What is the resulting increase in Sales ($ and %) from a treatment?
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| Jan 17, 2018 at 22:16 | vote | accept | Russ Harris | ||
| Dec 31, 2017 at 3:02 | review | First posts | |||
| Dec 31, 2017 at 3:14 | |||||
| Dec 22, 2017 at 17:43 | comment | added | Russ Harris | OK - I went ahead and dumped detail for all stores - not just the 10 test stores I was originally concerned with. Detail does not contain averages. THANKS FOR YOUR HELP! | |
| Dec 22, 2017 at 17:36 | history | edited | Russ Harris | CC BY-SA 3.0 |
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| Dec 22, 2017 at 17:22 | answer | added | IrishStat | timeline score: 1 | |
| Dec 22, 2017 at 17:19 | comment | added | whuber♦ | The advantages of tracking actual sales by store include (but are not limited to) (1) being able to assess the distribution of sales across all stores at each week and (2) being able to assess the correlations between sales, by store, from week to week. This makes powerful techniques like time series analysis available to you. | |
| Dec 22, 2017 at 17:16 | comment | added | Russ Harris | My bad - I pasted the average sales. I edited the question. Will I get better results if I use actuals instead of averages? | |
| Dec 22, 2017 at 17:14 | history | edited | Russ Harris | CC BY-SA 3.0 |
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| Dec 22, 2017 at 15:56 | comment | added | whuber♦ | If indeed the control stores were "very similar" to the test stores, then why are their total weekly sales almost the same despite having ten times as many control stores? Something's not consistent in your description. For the best analysis of this situation, you ought to examine the actual weekly sales of all 110 stores, not just their totals. | |
| Dec 22, 2017 at 15:44 | history | asked | Russ Harris | CC BY-SA 3.0 |