Sales for Seafood City ($)

Day

Week 1

Week 2

Monday

1,700

1,800

Tuesday

1,900

2,000

Wednesday

2,100

2,100

Thursday

2,300

2,200

Friday

4,200

4,300

Saturday

4,400

4,600

Sunday

2,100

2,200(Points : 4)        y = 2,092.31. + 81.98x
       y = 2,092.31 + 121.98x
       y = 1,892.31 + 81.98x
       y = 1,892.31 + 81.98x

Question 2. 2. (TCO 3) Using the following information regarding actual sales for Sam’s Ski Supplies, project sales for March of Year 3 using simple linear regression:  Sales for Sam’s Ski Supplies ($000s)MonthFirst YearSecond YearJanuary380400February340360March320330April280290May265270June230235July220230August200205September210220October250270November400450December450502(Points : 4)       308.62        326.94        328.61        330.28

Question 3. 3. (TCO 3) Using the following information regarding actual sales for Paradise Pools, calculate the seasonal ratio for June of Year 3:  Sales for Paradise Pools ($000s)MonthFirst YearSecond YearJanuary8484February8082March8898April100120May150160June200210July240250August220215September180195October160165November120130December92100(Points : 4)       0.67        0.77        1.08        1.41

Question 4. 4. (TCO 3) Using the following information regarding actual sales for Sam’s Ski Supplies, calculate the seasonal forecast of sales for November of Year 3:  Sales for Sam’s Ski Supplies ($000s)MonthFirst YearSecond YearJanuary380400February340360March320330April280290May265270June230235July220230August200205September210220October250270November400450December450502(Points : 4)       400        450        465        521

Question 5. 5. (TCO 3) The regression statistic that measures the accuracy of regression predictions is the: (Points : 4)

 

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