A B C D E F G H K L M N O P Q Bagel Purchase IN Daily customers # of bagels Prob LB UB Day # of Customers Random Demand per cust Daily Dem Profit Run Profit W mean 25 0.3 0 0.3 1 30 0.916346 90 $90.00 1 $1,667.00 4 std 5 0.45 0.3 0.75 2 21 0.121545 21 $58.50 2 $1,709.00 AWNH 0.2 0.75 0.95 30 0.179611 30 $90.00 3 $1,600.50 6 Quantity 30 0.05 0.95 1 25 0.866674 75 $90.00 4 $1,800.00 5 29 0.47832 58 $90.00 5 $1,663.50 8 Cost $1.00 6 33 0.482434 66 $90.00 6 $1,625.00 9 Price $4.00 7 18 0.043152 18 $48.00 7 $1,663.50 10 Salvage $0.50 8 19 0.993976 76 $90.00 8 $1,702.00 11 17 0.573114 34 $90.00 9 $1,698.50 12 1 Replication 10 23 0.149953 23 $65.50 10 $1,646.00 13 Monthly Profit $1,667.00 11 22 0.63715 44 $90.00 11 $1,744.00Daily customer traffic of a bagel shop follows a normal distribution with mean 25 and standard deviation 5 (integers). Each arriving customer can buy 1, 2, 3 or 4 bagels. From the past data, the baker derives the following probability distribution for average demand of bagels per customer: # of bagels probability 1 0.30 2 0.45 3 0.20 4 0.05 Each bagel costs $1 sells for $4. The shop produces 30 bagels daily and can salvage any unsold bagel at $0.5 at the end of each day. The shop is open 20 days in a month. This shop hires you to simulate 1 month (20 days) operation of this bagel shop to calculate the total monthly profit. You also replicate this calculation 200 times. Here's a screenshot from a part of your simulation:The above screenshot doesn't show the complete day and replication tables. What is the formula in cell J5? O=NORM.INV(RANDBETWEEN($B3,$B4) O=INT(NORM.INV(RAND().$B$3,$B$4)) O=NORM.INV(RAND(),$B$3,$B$4) O=NORM.INV(RAND(),B$4,B$3) =INT(NORM.INV(RANDBETWEEN($B$3,$B$4))