20221007ReviewForStudents

A CPA firm has two branch offices: downtown branch and suburban branch. During the last m to 14 April), the firm recruits college accounting majored students to meet the heavy demand. structure for each branch during the month's activities (only variable costs incurred): Downtown branch Large size 10 $6,000 4 $4,000 $1,200 Medium si 15 $4,000 3 $4,000 $1,200 Small size 20 $2,000 4 $4,000 $1,200 Suburban branch Large size 5 $5,000 2 $3,500 $1,200 Medium si 10 $3,500 3 $3,500 $1,200 Small size 30 $2,000 4 $3,500 $1,200 1. Downtown's productivity (multi-factor)? 2. Suburban's productivity (multi-factor)? 3. Overall's productivity (both branches together)? 4. Which group of students has the highest productivity (multi-factor)? # of customers processed Per customer's charge ($ inflow) # students needed Salary per month Health insurance per student # of customers processed Per customer's charge ($ inflow) # students needed Salary per month Health insurance per student

large size downtown? Medium size downtown? Small size downtown? Or, L.size suburban, M 5. This CPA firm believes Downtown Branch's low productivity from the small size's students size customers. Based on the productivity you have found in question 4, how many more sma students process (in addition to 20) to reach the same productivity as the one you have found f are allowed to process a fraction of an integer firm. 6. What is the new total productivity once the firm can process additional small size customer in question 5? 7. Which group of students has the highest productivity based on # firm/per student?

M. size suburban, S. size suburban? s is due to not having enough small all size customers should this group of from question 4? Assuming we rs from the answer you have found suburban small size

und of cumulative probability n 9,D10,H9) If begin inventory > demand, then your end inv = begin inv - demand, otherwise your end inv shou >0, BE-SD, 0) previous Begin Inv + Unit recd - previous demand Random # End Inv Simulated demand

uld be 0.

t (X) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1. The yellow-colored sales data's CMA should start from which cell # and end at whic 19 Cell # 20 Start: 21 End 22 23 24 Cell # 25 Start: 26 End 27 28 3. The yellow-colored sales data's regression output should have how many observatio 29 and how many degree of freedom? 30 # 31 Observation 32 df 33 34 4. The green-colored sales data's regression output should have how many observation 35 and how many degree of freedom? # Observation df 5. Which color's dales data will have fewer seasonal peaks if both of them exhibits a significant seasonal demand? 2. The green-colored sales data's CMA should start from which cell # and end at which

Week Day t (X) Year Month Week 1 1 1 Year 1 1 2 2 2 3 3 3 4 4 4 5 5 5 6 6 6 7 7 7 Week 2 1 8 8 2 9 9 3 10 10 4 11 11 5 12 12 6 13 Year 2 1 7 14 2 Week 3 1 15 3 2 16 4 3 17 5 4 18 6 5 19 7 6 20 8 7 21 9 Week 4 1 22 10 2 23 11 3 24 12 4 25 Year 3 1 5 26 2 6 27 3 7 28 4 Week 5 1 29 5 2 30 6 3 31 7 4 32 8 5 33 9 6 34 10 7 35 11 36 12

2.4 what is the procedure to answer the following question? If a project's 71.57% chance of on-time completion time is 16 weeks, what is a 99% chance of on-time completion time? 1st step: Solve what variable? 2nd step: Solve what variable?

etion

B 14 18 22 C 20 30 40 D 14 23 44 E 4 11 12 F 9 16 17 G 17 20 29

A. 10 B. 15 C. 10 D. 20 E. 20 F. 15 G.25 H. 10 Answer: Answer: Answer: Answer: Answer: (list any impossible