Coffee KSA! is opening a new location. Data from other locations suggests the fixed cost per week of runnin
a. Given these assumptions, what level of sales volume will enable Coffee KSA! to break even
b. Given these assumptions, discuss how a change in sales volume affects profit (one-way data table
c. Given these assumptions, discuss how a change in sales volume and variable cost jointly affet profit (
Coffee KSA!
e fixed cost per week of running the new location will be about SAR 1,000. It is predicted that the new location will sell 300 cup
break even?
way data table).
e cost jointly affet profit (two-way data table).
he new location will sell 300 cups per week at SAR 4 per cup. The variable cost of producing a cup of coffee is about SAR 1.
of coffee is about SAR 1.
Overhead Expenses
The table below contains data on
efficiency and trimming bureaucra
A) Construct a time series plot (i.e
B) Use simple linear regression an
C) Forecast the percentage of rev
D) If your organization can mainta
Year
2015
2016
2017
2018
2019
2020
2021
Expense (% of Revenue)
13.9
12.2
10.5
10.4
11.5
10
8.5
elow contains data on your organization’s annual overhead expenses. Beginning in 2015, you decided to initi
nd trimming bureaucratic excess.
t a time series plot (i.e. a scatter chart). What type of pattern exists in the data?
le linear regression analysis to find the parameters for the line that minimizes MSE for this time series.
the percentage of revenue that will be spent on overhead in 2023.
rganization can maintain its current trend in reducing administrative expenses, how long will it take to achiev
n 2015, you decided to initiate a comprehensive effort to reduce overhead by improving
E for this time series.
w long will it take to achieve a level of 5% or less?
Formula 1
This file contains data on the total accumulated
finishes (Top 10), top five finishes (Top 5
factors are most predictive of a driver’s winnings.
A) Run a regression model in which the dependen
1. How much variance in winnings is e
2. Which of our two independent vari
B) Run a regression model in which the dependent
3. How much variance in winnings is e
4. Which variable, if any, seems to be
5. If the answer to #4 above is differe
C) Run a regression model in which the dependent
6. How much variance in winnings is e
e total accumulated winnings of 35 Formula 1 drivers. The data can be found on the worksheet laballed, ‘Da
Top 5), first place finishes (Wins), and the total number of times the driver started in the pole position
of a driver’s winnings.
n which the dependent variable is ‘Winnings’, and the two independent variables are ‘Poles’ and ‘Wins’. Sav
ariance in winnings is explained by our model?
r two independent variables, if any, seems to be a stronger predictor of accumulated winnings?
n which the dependent variable is ‘Winnings’, and the three independent variables are ‘Poles’, ‘W
ariance in winnings is explained by our model?
ble, if any, seems to be a stronger predictor of accumulated winnings?
r to #4 above is different than the answer to #2, how do you explain the discrepancy?
n which the dependent variable is ‘Winnings’, and the four independent variables are ‘Poles’, ‘Wi
ariance in winnings is explained by our model?
worksheet laballed, ‘Data’. Among other variables, we have data on top ten
ted in the pole position (Poles). We are interested in identifying which
‘Poles’ and ‘Wins’. Save the output in a new worksheet.
winnings?
e ‘Poles’, ‘Wins’, and ‘Top 5’. Save the output on a new worksheet.
‘Poles’, ‘Wins’, ‘Top 5’, and ‘Top 10’. Save the output on a new worksheet.
Driver
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Points
2403
2403
2345
2330
2319
2304
2290
2287
2284
2284
2262
2246
1047
1041
1013
997
947
937
936
935
932
930
906
902
846
820
795
757
670
572
541
508
398
268
192
Poles
1
3
0
3
1
0
1
1
0
3
3
1
0
2
0
3
0
1
0
0
2
2
2
2
0
0
1
1
0
0
0
0
0
0
0
Wins
5
1
4
3
3
2
0
3
1
1
2
4
1
1
0
0
1
0
1
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
Top 5
9
19
9
12
10
14
4
13
5
9
8
14
4
8
1
3
4
3
5
2
2
2
4
4
3
2
2
1
1
1
0
1
0
0
0
Top 10
19
26
19
20
14
21
12
18
14
17
16
18
16
15
10
10
8
12
12
5
8
10
8
6
7
5
4
3
2
2
0
1
0
0
0
Winnings ($)
6,529,870
8,485,990
6,197,140
6,183,580
5,087,740
6,296,360
4,163,690
5,912,830
5,401,190
5,303,020
5,936,470
6,161,020
5,633,950
4,775,160
4,825,560
4,318,050
3,853,690
3,955,560
4,750,390
3,807,780
5,020,780
3,830,910
4,203,660
3,856,010
4,301,880
4,579,860
4,794,770
4,374,770
4,505,650
3,878,390
2,838,320
3,229,210
2,868,220
2,271,890
2,559,500
