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Case Background
Case Background
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This case is based on real financial data provided by a retail automobile dealership (Motomart) seeking to relocate closer to an existing retail
dealership. You’ll examine the mixed cost data from Motomart and apply both high-low and regression to attempt to separate mixed costs into
their fixed and variable components for break-even and contribution margin computations. You’ll find that the data is flawed because Motomart
was a single observation in a larger database. Don’t attempt to correct the data (e.g., remove outliers or influential outliers). You’ll be producing a
scatterplot and apply high-low and regression methods to the extent practicable and writing a summary report of the findings.
Motomart operates a retail automobile dealership. The manufacturer of Motomart products, like all automobile manufacturers, produces
forecasts. It has long been an industry practice to use variable costing-based/break-even analyses as the foundation for these forecasts, to examine
their cost behavior as it relates to the new retail vehicles sold (NRVS) cost driver. In preparing this financial information, a common financial
statement format and accounting procedures manual are provided to each retail auto dealership. The dealership is required to produce monthly
financial statements using the guidelines provided by this common accounting procedures manual, and then furnish these financial statements to
the manufacturer. General Motors, Ford, Nissan, and all other automobile manufacturers employ similar procedures manuals.
The use of a common format facilitates the development of composite financial statements that can be used to estimate costs and produce
financial forecasts for future or proposed retail dealership sites (Cataldo and Kruck 1998). Zimmerman (2003) suggests that as many as 77 percents
of manufacturers divide costs into variable and fixed components and that managers arrive at these estimates by classifying individual accounts as
being primarily fixed or primarily variable (67).
For this case, you’ll examine mixed costs as defined by the manufacturer. Using the scatterplot, high-low, and regression methods, separate these
mixed costs into their fixed and variable components. The data is problematic, and a clear solution won’t exist. Don’t attempt to correct the data
by removing outliers, but make observations based on any patterns you observe. The case will expose you to actual data and require you to
summarize your findings, including any conclusions you’re able to reach and why the financial data makes it impossible to separate the mixed
costs into their fixed and variable components.
Motomart: A Litigation Support Engagement
The Motomart case evolved from a litigation support engagement. The lead author of this case was hired to analyze the data and provide expert
testimony. His report and testimony was made available to the public (for a fee to cover reproduction costs). A broad description of the relevant
points for the Motomart case follows.
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Case Background
Motomart wanted to move their retail automobile dealership, blaming their location for declining profits and increasing losses. They provided
financial projections, using variable costing, to show that after the relocation both Motomart and the existing dealership would be profitable. They
created these financial projections using a database provided by the manufacturer, which included all North American retail automobile
dealerships. Motomart was one of the observations or retail automobile dealerships included in the database used to create these financial
projections. You’ll be examining portions of Motomart’s historical financial data.
The relocation site was quite close to the existing dealership (which we’ll refer to as Existing Dealer), and Existing Dealer felt that, if the relocation
was permitted, one or both of the dealerships would fail to break even and eventually go bankrupt, leading to poor service, or what the industry
refers to as “orphaned” owners of these automobiles.
Antitrust laws provided Existing Dealer with the means to block the relocation requested by Motomart, but only if it could prove that the relocation
wasn’t in the best interest of the consuming public. Generally, the only way to prove this is to prove that there’s simply not enough business for
both retail automobile dealerships to break even (or generate a reasonable return on investment, given the risks associated with the industry).
Again, the manufacturer, in support of the proposed Motomart relocation, supplied financial projections showing that both retail automobile
dealerships would be profitable after the relocation.
The expert witness hired to investigate the merits of the relocation was given the Motomart data, but not the entire database that included the
Motomart data. The Motomart data was in such poor form that it wasn’t possible to produce a financial forecast. An alternative forecast, not
included in this case, was produced. This alternative forecast did not support the relocation of Motomart to a site closer to Existing Dealer. The
alternative forecast showed that the market simply couldn’t support two retail automobile dealerships. The implication was that, as the weaker of
the two dealerships, Motomart was losing business to Existing Dealer. In conclusion, the relocation request by Motomart was denied.
Income and Expense Data
The following tables give you information such as income statements, semi-fixed expenses, and salaries for Motomart. Look for unusual entries or
discrepancies in their records and, where you can, note the cause of the problems.
Table 3 summarizes financial and cost driver information produced by Motomart, where new retail vehicles sold (NRVS) is the cost driver. The
account classification method has resulted in three cost behavior classifications: variable, semi-fixed, and fixed costs. Semi-fixed is the automobile
industry-specific term used for mixed costs. We’ll assume that Motomart’s classifications of variable costs (VCs) and fixed costs (FCs) are correct,
and focus our analysis on Motomart’s semi-fixed or mixed costs.
Table 2
SElECTED HISTORICAl INCOME STATEMENT AND RElATED MEASURES
2014
2015
2016
2017
2018
2,885,969
3,828,255
4,086,667
3,940,799
4,298,748
Salaries
613,006
968,789
1,211,464
1,289,758
1,360,489
Vacation
600
26,705
19,468
19,059
18,268
Advertising & Training
210,226
288,347
281,219
309,608
371,314
Supplies/Tools/Laundry
31,473
46,141
75,468
65,935
81,252
Net Variable Revenues*
Semi-Fixed (S-F) Expenses:
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Case Background
Freight
5,719
5,987
6,528
5,731
4,663
Vehicle
22,913
23,718
23,664
20,370
19,483
Demonstrators
10,465
4,969
-1,513
4,192
707
Floor-Planning
278,531
301,113
276,201
156,129
305,044
Total S-F Expenses
1,172,933
1,665,769
1,892,499
1,870,782
2,161,220
Total Fixed Expenses
1,449,208
2,050,172
2,290,867
2,164,362
2,653,620
Operating Profit/(Loss)**
263,828
112,314
-96,699
-94,345
-516,092
New Retail Vehicles Sold
1,798
1,977
1,674
1,450
1,897
Fixed Expenses:
Notes:
* Revenues less variable costs equal Net Variable Revenues (or Contribution Margin, in aggregate).
** Net Variable Revenue less Total S-F Expenses less Total Fixed Expenses equals Operating Profit/(Loss).
Table 3 provides five years of monthly data (N=60) for NRVS and the related semi-fixed or mixed cost measures. Semifixed costs were significant.
Recall that they ranged from nearly $1.2 million for calendar and fiscal year (FY) 2014 to almost $2.2 million for FY 2018 (see Table 2).
Table 3
SEMI-FIXED (MIXED) EXPENSES FOR THE 60-MONTH PERIOD (FY 2014 THROUGH 2018)
Mo
NRVS
Salary
Vacation
Adv/Trng
SplyTls/Lndry
1
197
$ 52,951
$
–
$ 22,561
$
1,118
2
133
$ 47,054
$
–
$ 19,040
$
3,573
3
132
$ 55,372
$
–
$ 14,373
$
1,388
4
141
$ 46,114
$
–
$ 15,022
$
2,894
5
182
$ 48,309
$
–
$ 19,966
$
1,896
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6
156
$ 49,643
$
–
$ 12,019
$
1,188
7
196
$ 55,784
$
300
$ 13,217
$
3,912
8
178
$ 47,957
$
–
$ 17,303
$
2,012
9
159
$ 53,743
$
–
$ 16,535
$
2,717
10
141
$ 53,109
$
–
$ 23,821
$
1,102
11
152
$ 45,491
$
300
$ 14,146
$
2,630
12
31
$ 57,479
$
–
$ 22,223
$
7,043
13
280
$ 49,049
$
–
$ 19,992
$
1,999
14
136
$ 46,698
$
300
$ 20,251
$
1,192
15
174
$ 59,790
$
200
$ 20,082
$
1,336
16
171
$ 80,773
$
600
$ 26,716
$
3,873
17
167
$ 71,130
$ 9,212
$ 25,223
$
5,560
18
161
$ 82,490
$ 6,007
$ 21,106
$
1,737
19
173
$ 98,172
$
500
$ 17,799
$
1,847
20
161
$ 90,685
$ 2,690
$ 28,038
$
4,415
21
167
$ 97,771
$
600
$ 37,284
$
2,827
22
153
$ 87,129
$ 1,740
$ 24,236
$
5,836
23
201
$ 95,910
$ 2,074
$ 27,244
$
3,387
24
33
$ 09,192
$ 2,782
$ 20,376
$ 12,132
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25
227
$ 89,041
$ 1,880
$ 26,719
$
26
150
$ 92,165
$ 3,602
$ 14,727
$ 10,231
27
142
$ 88,981
$
744
$ 27,880
$
7,734
28
104
$ 95,898
$
960
$ 21,872
$
(684)
29
121
$ 96,245
$
–
$ 18,705
$
8,329
30
99
$ 106,364
$
–
$ 23,835
$
2,540
31
150
$ 90,564
$ 1,950
$ 25,605
$
5,862
32
144
$ 98,418
$ 1,540
$ 17,763
$
6,998
33
154
$ 110,436
$ 2,693
32,379
34
130
$ 102,042
$ 1,060
$ 19,324
$
6,026
35
202
$ 124,413
$ 3,519
$ 22,412
$
9,120
36
51
$ 116,897
$ 1,520
$ 29,998
$
6,798
37
148
$ 97,083
$ 1,080
$ 9,112
$
6,627
38
153
$ 104,727
$ 3,230
$ 38,616
$
5,892
39
83
$ 95,622
$
953
$ 22,690
$
3,450
40
101
$ 96,438
$ 1,244
$ 14,703
$
5,259
41
140
$ 114,995
$
–
$ 28,764
$
2,294
42
132
$ 105,337
$
160
$ 27,253
$
8,155
43
112
$ 98,989
$ 2,480
$ 24,419
$
1,621
$
4,383
8,131
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44
127
$ 124,352
$ 1,800
$ 26,011
$
902
45
139
$ 115,875
$ 1,417
$ 24,492
$
5,158
46
156
$ 113,035
$ 1,820
$ 31,158
$
2,901
47
126
$ 119,106
$ 3,338
$ 32,213
$ 14,426
48
33
$ 104,199
$ 1,537
$ 30,177
$
9,250
49
209
$ 98,938
$ 1,866
$ 26,737
$
1,694
50
124
$ 108,606
$ 3,676
$ 31,084
$
9,040
51
131
$ 106,396
$ 1,197
$ 33,278
$
2,099
52
144
$ 106,778
$
241
$ 32,657
$
9,328
53
93
$ 124,805
$
500
$ 29,794
$
4,268
54
199
$ 110,153
$ 1,910
$ 38,431
$
5,407
55
170
$ 117,276
$
800
$ 27,640
$
9,305
56
186
$ 112,055
$
980
$ 28,657
$
1,803
57
200
$ 114,765
$ 1,695
$ 36,425
$
8,839
58
146
$ 128,007
$ 1,560
$ 27,720
$ 10,944
59
222
$ 116,811
$ 2,249
$ 27,941
$
60
73
$ 115,899
$ 1,594
$ 30,950
$ 30,950
5,775
Table 3 Continued
SEMI-FIXED (MIXED) EXPENSES FOR THE 60-MONTH PERIOD (FY 2014 THROUGH 2018)
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Case Background
Mo
Freight
Vehicles
Demo’s
Floor-Plan
Total
1
$
382
$ 2,052
$
1,881
$ (78,173)
$
2
$
409
$ 1,405
$
695
$
28,456
$ 100,632
3
$
742
$ 1,380
$
469
$
34,423
$ 108,147
4
$
675
$ 2,057
$
125
$
5,697
$ 72,584
5
$
572
$ 1,603
$
131
$
34,599
$ 107,076
6
$
407
$ 2,524
$
1,229
$
53,737
$ 120,747
7
$
643
$ 2,348
$
1,206
$
5,507
$ 82,917
8
$
605
$ 1,208
$
436
$
32,436
$ 101,957
9
$
209
$ 2,400
$
1,476
$
28,950
$ 106,030
10
$
184
$ 2,076
$
1,168
$
20,876
$ 102,336
11
$
331
$ 1,677
$
635
$
45,278
$ 110,488
12
$
560
$ 2,183
$
1,014
$
66,745
$ 157,247
13
$
582
$ 1,927
$
(477)
$ (30,104)
$ 42,968
14
$
603
$ 1,156
$
1,839
$
50,583
$ 122,622
15
$
492
$ 1,898
$
1,260
$
18,803
$ 103,861
16
$
559
$ 1,808
$
510
$
23,080
$ 137,919
17
$
356
$ 1,816
$
2,350
$
18,774
$ 134,421
18
$
439
$ 1,384
$
(288)
$
23,802
$ 136,677
2,772
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19
$ 1,628
$ 1,962
$
1,591
$
33,848
$ 157,347
20
$
(12)
$ 2,446
$ (3,308)
$
13,480
$ 138,434
21
$
480
$ 2,296
$
1,709
$
22,965
$ 165,932
22
$
79
$ 3,175
$
798
$
18,898
$ 141,891
23
$
188
$ 1,287
$ (2,025)
$
38,699
$ 166,764
24
$
593
$ 2,563
$
1,010
$
68,285
$ 216,933
25
$
769
$ 2,205
$
2,493
$ (44,140)
$ 83,350
26
$
593
$ 2,289
$ (2,051)
$
36,311
$ 157,867
27
$
414
$ 1,891
$
386
$
19,865
$ 147,895
28
$
425
$ 2,288
$
178
$
19,013
$ 139,950
29
$
483
$ 2,223
$
(262)
$
16,228
$ 141,951
30
$
417
$ 1,683
$ (1,356)
$
37,637
$ 171,120
31
$
222
$ 1,586
$
(1,121)
$ 125,154
32
$
49
$ 1,751
$ (1,924)
$
34,757
$ 159,352
33
$
818
$ 2,082
$
1,547
$
26,419
$ 184,505
34
$ 1,015
$ 1,714
$
132
$
21,134
$ 52,447
35
$ 1,255
$ 2,173
$ (2,337)
$
18,578
$ 179,133
36
$
68
$ 1,779
$
1,195
$
91,520
$ 249,775
37
$
565
$ 1,324
$
1,164
$ (73,753)
$ 43,202
486
$
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38
$
369
$ 1,523
$ (1,839)
$
30,443
$ 182,961
39
$ (182)
$ 2,087
$
454
$
17,725
$ 142,799
40
$
709
$ 2,095
$
868
$
26,402
$ 147,718
41
$ 1,006
$ 1,304
$ (1,990)
$
(3,789
$ 142,584
42
$
521
$ 1,667
$
1,869
$
15,090
$ 160,052
43
$
514
$ 1,040
$
329
$
(945)
$ 128,447
44
$
917
$ 2,880
$ (1,897)
$
30,405
$ 185,370
45
$
(77
$ 1,281
$
2,959
$
14,781
$ 165,886
46
$
450
$ 2,259
$
417
$
15,613
$ 167,653
47
$
120
$ 1,394
$ (2,659)
$
40,968
$ 208,906
48
$
819
$ 1,516
$
4,517
$
43,189
$ 195,204
49
$
853
$ 1,657
$
601
$ (20,127)
$ 112,219
50
$
498
$ 2,266
$
(284)
$
18,236
$ 173,122
51
$
605
$ 1,952
$
668
$
15,176
$ 161,371
52
$
483
$ 1,852
$
1,409
$
25,245
$ 177,993
53
$
788
$ 1,704
$ (1,771)
$
6,493
$ 166,581
54
$
529
$ 1,882
$
453
$
21,851
$ 180,616
55
$ (180)
$ 977
$
1,310
$
7
$ 157,135
56
$
$ 846
$ (2,844)
$
17,192
$ 158,447
242)
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Case Background
57
$
859
$ 2,856
$
1,532
$
14,864
$ 181,835
58
$ (492)
$ 1,864
$
1,400
$
10,121
$ 181,124
59
$
245
$ 1,141
$ (3,513)
$
7,946
$ 158,595
60
$
717
$ 486
$
$ 188,040
$ 352,182
1,746
Recall the cost function applying to the high-low and regression methods, which are provided in a variety of forms, depending on the texts you
used in your previous math, economics, or accounting courses. Below is a brief outline of the high-low and regression methods.
For the high-low method to work, the $H and #H and the $L and #L measures must be from the same accounting period.
Preparing Graphs
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Case Background
The single cost driver and nonfinancial measure in Table 3 is new retail vehicles sold (NRVS or X in the above cost function). There are eight
financial measures (salary; vacation; advertising and training; supplies, tools, and laundry; freight; vehicles; demonstrators; and floor-planning
[also known in the automobile retail industry as interest expense relating to new car inventory]), as well as a total (aggregate measure) provided
for all eight financial measures (or the Y in the above cost function).
Using NRVS, the only available cost-driver, use Excel to prepare nine separate scatter plots and cost function-based trend lines and nine separate
line graphs for each of the financial measures provided in Table 3. The images below are an example of completed graphs for salaries.
A Scatterplot Graph for Motomart Salaries
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Case Background
A Line Graph for Motomart Salaries
Now examine, on a preliminary basis, the pattern or trend (or lack thereof ) for each of the “X” (NRVS) and “Y” (financial measure) data pairs and
consider the following questions:
You’re observing these data pairs for a 60-month period (i.e., five years); are any annual or other seasonal patterns or trends
immediately apparent?
Do the slopes of the trend lines (i.e., variable costs) make sense?
In the case of salaries (see the graphs above), there’s no apparent trend or pattern. It’s odd that salaries decrease as NRVS increases—in fact, this
doesn’t make any sense. However, it’s consistent with the high-low results, which also didn’t make sense. But remember, since this data came from
Motomart, the firm attempting to relocate, it’s real and from an actual litigation support engagement (not a textbook problem), so it won’t
necessarily work out perfectly.
The cost equation in Table 4 shows fixed costs (FC) at $106,866.00 and variable costs to be used to “reduce” total costs (TC) by $110.10 per NRVS.
Compare the salary figures and coefficients (in bold type) to the scatterplot graph for Motomart Salaries. Notice that if you extended the trend line
in Figure 4, it would hit the y-axis intercept at $106,866.00 (the fixed cost). Also, notice that the R-squared (R-sq) measure in Table 4 equals 4.1
percent.
Table 4
SALARY = $106,866.00 – $110.10 NRVS
Predictor
Coefficient
Std Deviation
t-statistic
p-value
Constant
106,866.00
10,793.00
9.90
0.000
NRVS
110.10
70.17
–1.57
0.122
s = 25300
r-sq = 4.1%
Analysis of Variance
SOURCE
DF
SS
MS
Regression
1
261,795
261,795
Error
58
152,801,120
2,634,502
Total
59
153,062,912
F-
p-
statistic
value
0.10
0.754
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Case Background
Your math and statistics courses probably reviewed the use of the t-statistic, overall F-statistic, and related p-values, as well as some of the other
measures presented here. Our application is a very simple one, so we’ll focus on only the R-squared measure. The other measures are provided in
this example only for completeness.
Because the high-low technique didn’t work, it makes sense that the regression technique wouldn’t work well, either. Therefore, the results for
high-low and regression are consistent. The advantage of the regression technique is that it mathematically quantifies the level of the problem or
difficulty with the data. In this case, one of simple regression, the R-squared measure tells the story. Still focusing on the salaries example in Figure
5, the R-squared measure tells us that only 4.1 percent of the total or mixed or semi-fixed cost is explained by NRVS. This means that that cost
equation developed from this historical data isn’t helpful in predicting future costs, as nearly 96 percent of the cost behavior, through use of this
equation, remains unexplained.
Requirements
The project requires five steps to be presented.
Step 1 – Provide comments on a 5-year Income Statement.
Step 2 – Discuss patterns in expense items.
Step 3 – Identify High/Low activity levels.
Step 4 – Compute cost equations.
Step 5 – Summarize your findings.
In one Word document, provide individual sections for each Step. This Word document along with the Excel file (described below) will be
uploaded when you click on the Take Exam button on your Student Portal to submit your project (described under “Submitting Your Assignment”
later in the instructions).
This Senior Capstone project highlights your knowledge and the skills you have developed over the course of your education. There is nothing
“new” to be learned here.
The knowledge and skills required for this project include English Composition, Financial Accounting, Managerial Accounting, Business Statistics
and the abilities to think critically and to present your work in a professional manner.
If you are unsure or don’t understand something about the project, then go back to your previous subjects to review. For example, if you don’t
remember how to use the High/Low Method, the revisit your Managerial Accounting to refresh your memory on how to use the High/Low Method
Remember, there is nothing “new” here. Everything about this project you should already know how to do.
At the beginning of the assignment, on the right-hand side under “Optional Study Materials” select the “PPMC Excel Spreadsheet” menu item to
download the required Excel spreadsheet.
The Excel file provides a detailed example of what needs to be done for one of the expenses in order to fill out the figures required in
Steps 3 & 4. You will include this Excel file as part of your project submission along with the Word document you create to present this
project.
There is a “60 Months” worksheet that has the 60 months of data already entered. There is also a “Sample” worksheet that
an example of how to calculate the R-sq.
There is a “PLOT – SALARY” worksheet that shows how the FC, VC and R-sq figures are calculated for Salary.
There is also a “high&low” worksheet for help with the high/low method in Step 3.
Complete and include the Excel spreadsheet. You will need to create new worksheets for each of the other expenses
following the example to calculate the figures needed for Table 5.
Operating Profits and Semi-Fixed Expenses
Step 1
First, using Tables 2–4, note the pattern of operating profits (or losses) over the five-year period. Then focus only on the semi-fixed expenses
contained in Table 2. Do any amounts appear to be odd? (Think about whether the figures are right or wrong. What is it about the individual
numbers that is not “right”?) Next, briefly comment on the five-year pattern or trend for operating profit/loss measures. You should be able to
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Case Background
respond to this step in a few well-written sentences.
Step 2
Focus only on the detailed semi-fixed expense contained in Table 3. Are there any unusual or odd patterns you might note in this detailed financial
data? There are 5 expenses that have an oddity about them which doesn’t make sense. Similar to Step 1, what is it about the individual numbers
that are not “right”? There are 4 expenses that “stick out” as not being correct and one that has an unusual pattern. You should be able to respond
to this requirement in a few well-written sentences. Briefly comment on only the most obvious or apparent measures or patterns, by expense item.
Step 3
Identify the high and low measures in each column, just as you would in preparation for the application of the high-low method or technique. For
example, in Table 3 the high measure for the cost driver (NRVS) is 280 NRVS in month 13 and the low measure is 31 NRVS in month 12. Repeat this
process for each of the eight separate semi-fixed expense columns and also for the total expense column. Insert a table for Step 3 to present your
findings. The table should have three columns;
1. Expense
2. High Figure
3. Low Figure
After the high and low measures have been identified in each column, try to match each expense column’s high and low measure, separately, to
the highs and lows identified in the NRVS column. They won’t match. Don’t try to correct the data, but comment on the potential for application of
the high-low technique. What happens when the high and low activity level doesn’t match the high and low expense measure? Does this prevent
you from correctly applying the high-low technique?
Don’t overanalyze this data, because there’s a problem with it and you don’t have sufficient information to correct it. Merely summarize your
observations and unsuccessful attempts to match the high and low NRVS months (identified above), separately, with each of the high and low
expense measure months. You should be able to do this in a very few well-written sentences.
Step 4
Using the Excel file “Exam 500896 – Motomart Excel Spreadsheet” as per the instructions found above under the “Project Requirements”,
reproduce and complete the following Table 5 and answer the four questions. The Excel file provides an example of how to arrive at the figures that
need to be entered into the Table. You will create new worksheets for each of the remaining expenses. Do the work to arrive at the figures for each
expense. Be sure to include the Excel file as part of your submission to “backup” the data presented in the Table in the Word document being
submitted.
The Excel spreadsheet, while it will be included in your submission for the project, will not be graded. It is supporting documentation for what is
being presented in the Word document. Only the information that is in the Word document will be graded.
The FC and VC should be rounded to the nearest dollar. The R-sq is a percentage figure carried out to 2 decimal places.
Table 5
Column
Expense
1
Salaries
2
Vacation
3
Advertising and training
FC
VC
R-sq
$106,866
–$110
4.10%
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Case Background
4
Supplies/tools/laundry
5
Freight
6
Vehicles
7
Demonstrators
8
Floor planning
Computed total
9
Total
Complete the cost equations for the table. Use the R-squared as the single measure of “goodness of fit.” Don’t attempt to improve your results with
the elimination of “outliers” or “influential outliers.” As you complete Table 5, answer the following questions:
1. What problems did you encounter?
2. Are the R-squared measures high or low?
3. Are the slopes negative or positive?
4. Are your conclusions consistent with those from the high-low effort?
Step 5
Summarize your findings by answering the following questions:
1. Can the Motomart data be used to prepare a reliable financial forecast? Why or why not?
2. If Motomart is included in the very large database used to prepare the financial forecast that supports the relocation of Motomart
closer to Existing Dealer, what concerns might present themselves with respect to the remainder of the database used for this
forecast?
3. Would you rely on this forecast?
Writing Guidelines
Refer to the “Submitting Your Work” section at the end of this book for details on submission requirements for the Motomart Case assignment.
Grading Criteria
Your assignment will be evaluated according to the following criteria:
Content
80 percent
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Case Background
Written Communication
10 percent
Format
10 percent
Criteria
Grade
Content 80 pts
Step 1 – Provides comments on 5-year income statement (worth 10 points)
Step 2 – Discuss patterns in expense items (worth 10 points)
Step 3 – Identify high and low activity levels (worth 10 points)
Step 4 – Compute cost equations (worth 30 points)
Step 5 – Summarize your findings (worth 20 points)
Written Communication 10 pts
Answers each question in complete sentences leading to well-structured responses to
each Step listed above.
Uses correct grammar, spelling, punctuation, and sentence structure
Provides clear organization by using words like first, however, on the other hand, and so
on, consequently, since, next, and when
Makes sure the paper contains no typographical errors
Format 10 pts The paper is double-spaced, typed in font size 12. It includes the student’s
Name and address
Student number, Course title and number, and project number
Total Grade
%
Submitting Your Work
1. Type your submission, double-spaced, in a standard print font, size 12. Use a standard document format with 1-inch margins. (Do not
use any fancy or cursive fonts.)
2. Include the following information at the top of your paper:
a. Name and complete mailing address
b. Student number
c. Course title and number (Senior Capstone: Business, BUS 450)
d. Project number (see Format instructions)
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Case Background
e. Project title (Professional Development Activity, Case 1, etc.)
3. Read the assignments carefully and complete each one in the order given.
4. Be specific. Limit your submission to the questions asked and issues mentioned.
5. If you include quotes or ideas from textbooks or other sources, provide a reference page in either APA or MLA style. On this page, list
books, Web sites, journals, or any other references used in preparing the paper.
6. Proofread your work carefully. Check for correct spelling, grammar, punctuation, and capitalization.
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MONTH
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
36
37
38
39
40
41
42
43
44
45
NRVS (X)
197
133
132
141
182
156
196
178
159
141
152
31
280
136
174
171
167
161
173
161
167
153
201
33
227
150
142
104
121
99
150
144
154
130
202
51
148
153
83
101
140
132
112
127
139
SALARY (Y)
197
133
132
141
182
156
196
178
159
141
152
31
280
136
174
171
167
161
173
161
167
153
201
33
227
150
142
104
121
99
150
144
154
130
202
51
148
153
83
101
140
132
112
127
139
52,951
47,054
55,372
46,114
48,309
49,643
55,784
47,957
53,743
53,109
45,491
57,479
49,049
46,698
59,790
80,773
71,130
82,490
98,172
90,685
97,771
87,129
95,910
109,192
89,041
92,165
88,981
95,898
96,245
106,364
90,564
98,418
110,436
102,042
124,413
116,897
97,083
104,727
95,622
96,438
114,995
105,337
98,989
124,352
115,875
XY
52,951
47,054
55,372
46,114
48,309
49,643
55,784
47,957
53,743
53,109
45,491
57,479
49,049
46,698
59,790
80,773
71,130
82,490
98,172
90,685
97,771
87,129
95,910
109,192
89,041
92,165
88,981
95,898
96,245
106,364
90,564
98,418
110,436
102,042
124,413
116,897
97,083
104,727
95,622
96,438
114,995
105,337
98,989
124,352
115,875
10,431,347
6,258,182
7,309,104
6,502,074
8,792,238
7,744,308
10,933,664
8,536,346
8,545,137
7,488,369
6,914,632
1,781,849
13,733,720
6,350,928
10,403,460
13,812,183
11,878,710
13,280,890
16,983,756
14,600,285
16,327,757
13,330,737
19,277,910
3,603,336
20,212,307
13,824,750
12,635,302
9,973,392
11,645,645
10,530,036
13,584,600
14,172,192
17,007,144
13,265,460
25,131,426
5,961,747
14,368,284
16,023,231
7,936,626
9,740,238
16,099,300
13,904,484
11,086,768
15,792,704
16,106,625
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
1830
156
126
33
209
124
131
144
93
199
170
186
200
146
222
73
8796
156
126
33
209
124
131
144
93
199
170
186
200
146
222
73
113,035
119,106
104,199
98,938
108,606
106,396
106,778
124,805
110,153
117,276
112,055
114,765
128,007
116,811
115,899
5,443,506
a=
833,661,258,912
7800984
106,866
b=
(858,909,996)
7800984
r=