## Compare How Different Areas of Your Casino are doing using an Independent T-Test!

What if you wanted to compare different areas with different numbers of machines on your gaming floor? What if you wanted to know if a certain area was receiving more profit than another? In a previous post, we looked at how we can measure the effects of a change in machine settings on the earnings of a group of slot machines, using a dependent T-Test. For the post, see here: https://excelpunks.com/comparisons-using-t-tests/ If you recall, a dependent T-test compares the differences in means of data with identical sample sizes before and after treatment – our data being the earnings of a slot machine and the treatment being a change in settings. An independent T-test allows us to compare data sets with different numbers of samples to determine if they are statistically different. Here’s an example: A casino has 2 slot zones, Zone 1, with 5 machines and Zone 2, with 10 machines.  We want to find out if one area is

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## Find out if your latest marketing programme worked (or not) with the T-Test!

Do you need to compare results of an experiment or a marketing plan?  Have you just changed the settings of your slot machines and aren’t sure whether the change resulted in a real difference in earnings?  Have you just completed an intensive player promotion programme and need to find out whether it was effective? Statistics has a simple way of calculating if the revenue before and after resulted in a real change in performance and also the probability that the change was a DIRECT result of the changes you made!  This method is known as a T-Test. A T-Test compares the averages of 2 sets of values and assesses how different the sets of data are.  A companion to this is the R² measure of effect size, which calculates how much in terms of percentages that the results of your T-Test was affected directly by the change you implemented. Here’s an example: Casino A recently changed the settings of its

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