![]() ![]() If I include them, then they are outliers that throw everything off. How should I deal with the holidays that the restaurant was closed for? If I remove them, then the week lengths will not be the same.You can easily track your sales over a period of time and see all of the relevant information. What can I do to capture "long weekend effects"? Should I included a dummy variable for every Friday that proceeds a long weekend etc? With DailySales application, you will have a better overview of your sales.I think I should include the month of the year as a dummy variable to capture yearly seasonal effects as well. Sign up for the email list to get a coupon code good for free shipping on your first order as well as news about special promotions. Youll find items as high at 88 off the retail price. Column Name Column Type Short description Date string Date of sales summary Name string Name of sales person. Given this, write a SQL query to return the top sales person on each given day. You can assume the table is called DailySales. The section records all the money received from the days sales. Ma1 sar1 sma1 Mon Tue Wed Thu Day Newyears FamilyDay GoodFriday Easter VictoriaDay CanadaDay CivicDay You are given the following dataset of daily sales from a companys sales team. Daily Sales/Deposit Form On the lower part of the form, fill in the Cash in Register section. Further, I'm including the holidays as days with sales equal to zero, so this must throw off the model. I haven't done anything to take into account the effect of a holiday on the surrounding days. The model fit is not very good so far, of course. The difference is that I'm using only Mon-Fri, so my frequency is 5, and I've added dummy variables for all of the days that the restaurant is closed (holidays). I've followed the approach suggested by Rob Hyndman here. My approach has been to use a ARIMAX model to fit the data (using R). Sales are lower in the summer, for example, presumably, in part, because many office workers are taking their vacations. An example of this: if Monday is a holiday, sales tend to be much lower on the Friday before that long weekend - presumably office workers leaving work early. You might notice that there are sales spikes before or after certain holidays. Furthermore, the presence of a holiday changes the sales pattern in the surrounding weeks (the week before and the week after). There is definitely a weekly pattern: sales tend to peak on Thursdays. ![]() The days with zero sales, as you can see above, are the days that the restaurant was closed due to a public holiday (Easter Monday etc.). They are only open on business days - no holidays or weekends - as their primary clients are office workers on their lunch breaks.īelow is what two years of the daily sales time series looks like. I am trying to model daily sales for a take out restaurant. ![]()
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