The restaurant Eatin Good has a lunch special that is in direct competition with the nearby restaurant Eatin Well. In January 2019, both restaurants will change the price of their lunch special. Eatin Good will have a new price of $7.50 per lunch special, and believes Eatin Well will price their special according to a normal distribution with a mean of $7.6 and a standard deviation of $0.20$. There are 3 types of customers that will eat at these restaurants. Type 1 customers will always eat at Eatin Good no matter what. Type 2 customers will always eat at Eatin Well no matter what. Type 3 customers will always choose the lowest priced lunch special between the two restaurants and eat there. 40% of customers are Type 1 customers, 40% of customers are Type 2 customers, and the remaining 20% are Type 3 customers. The number of expected customers in January follows a uniform distribution between 4,000 to 6,000. Simulate 10,000 trials of January lunches and report back the following.

(a) Average, Max, and Min profit at Eatin Good for the month of January

(b) Number of times Eatin Good had less revenue than Eating Well for January.

To help you set up this simulation inside of SAS, the following partially censored template is provided. You can choose to build off of this template, or create your own simulation code from scratch. In the template, the numLess variable in line 7 aims to count the number of times Eatin Good had less revenue than Eatin Well in the month of January