# What type of regression analysis should I use for data concerning restaurant reservations

I am writing my thesis and am stuck on the data-analysis part. I want to find out how having a reservation influences revenue.

I want to find out whether guests with a reservation spend more time at the table than walk-in customers, and whether they spend more money. After that I would like to find out whether the day of the week has an influence on either of these findings (weekday or weekend), whether time of eating should be taken into account (lunch or dinner) and whether being a first time visitor or returning influences the outcome.

I have a large dataset (8240), cleaned up and ready to be used. It includes:

• Minutes spend at the table
• Spending per person
• Dummy variable whether lunch (0) or dinner (1)
• Dummy variable whether walk-in (0) or reservation (1)
• Dummy variable whether single (0) or returning visitor (1)

Any suggestions/ideas on how to handle this? I have done a multiple regression analysis but am not sure how to include the different factors correctly. I can use Excel or R.

– user10619
Jun 18, 2017 at 9:44
• What you have done seems a good start. If you are using R then declare your three predictors as factors and R will take care of things for you. Jun 18, 2017 at 10:44
• Be sure to plot and analyze the residuals Jun 18, 2017 at 11:07
• I have added the output I got after declaring the three as factors Jun 18, 2017 at 13:33
• plot(model1) will generate a series of useful diagnostic plots. Those plots include a lot of information, so you might contact your university's statistics department to see if you can get a tutor or consultation for an hour or so. Because of that long right tail, pay special attention to Cook's distance (see this nice answer here: stats.stackexchange.com/a/206330/68397). Depending on your exact research question, cross validation or robust regression (stats.stackexchange.com/a/104371/68397) might be worthwhile. Jun 18, 2017 at 14:21