| Course | AC570 Data Analytics for Accountants |
|---|---|
| Unit | Unit 4 |
| Paper type | Population profiling exercise |
| Length | About 580 words, 5 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | MS in Accounting |
| Updated | October 2026 |
Free sample paper for AC570 Unit 4
Seven Missing Days No Annual Total Would Show: A Unit 4 Population Profiling Exercise for a Storage Ledger
[Student Name]
Purdue University Global
AC570: Data Analytics for Accountants
Unit 4 Population Profiling Exercise
[Instructor Name]
[Date]
Stowfield Storage and every figure are composite; the textbook, guide and article cited are real.
Scope
Thirty-one facilities, January 1 to December 31, 2025, 413,896 prepared rows from the Unit 3 log, extracted January 14, 2026. The profile answers one question: is this file complete and consistent enough for the exception tests and regression that follow?
Panel 1: Coverage
A grid of 31 facilities by 12 months, each cell shaded by the share of days with any ledger activity, covers 11,315 facility-days, built from a table with one row per facility per day (Wickham, 2014). Every cell is full except Facility 27 in March. From March 3 to March 9, Facility 27 shows no payments, credits or charges. Its March payment count is 490, against 638 in February and 635 in April. The facility manager reports that the point-of-sale terminal failed and payments were taken on paper during that week; the paper receipts were never keyed into the ledger. Payments for those seven days appear only as a lump deposit in the bank.
Annual totals would not show this. Facility 27's year looks normal, and its March revenue is close to plan because the deposit was booked directly to cash. Only counting activity by day exposes the hole.
Panel 2: Field Completeness
For each field the later tests need, the share of rows where it is populated. Timestamps, tenant identifiers, amounts and facility codes are complete. Credit reason codes are blank on 214 credits, already typed "other" in preparation. Refund check numbers are blank on 41 of 3,223 refunds, all electronic transfers, which carry a transfer reference instead. Void flags are complete.
Panel 3: Credit Type Mix
Promotions are 44 percent of credit dollars, fee waivers 31 percent, goodwill 14 percent, corrections 9 percent and other 2 percent. The mix is stable across months except June, when goodwill doubles at Facility 22, a pattern the later tests will examine.
Panel 4: Month-by-Month Tie
Credits, payments and refunds by month tie to the general ledger in every month except December, where the $2,950 property-tax pass-through entry explained in the preparation log appears. March payments at Facility 27 are short in the ledger by the amount of the paper week, roughly 148 payments or about $21,000, which was booked to cash outside the tenant ledger.
Panel 5: Distribution Checks
Credit amounts range from $1 to $2,400, with the median at $96. Payment amounts follow the expected spread of monthly rents. No amounts are negative after typing.
The file is complete enough to test except for one facility-week, and the profile's job is to say exactly where that exception lies, so later tests can exclude Facility 27 in March rather than draw conclusions from a month that is missing a week of activity.
Verdict
The population is fit for testing with one exclusion: Facility 27's March data is incomplete and will be left out of the regression and noted wherever it would affect a test. The receipt sequence test should treat Facility 27's March gap as explained by the terminal outage, not as missing receipts. Profiling first prevents later tests from reporting a data problem as a business problem (American Institute of Certified Public Accountants, 2017; Richardson et al., 2023).
References
American Institute of Certified Public Accountants. (2017). Guide to audit data analytics. AICPA.
Richardson, V. J., Teeter, R. A., & Terrell, K. L. (2023). Data analytics for accounting (3rd ed.). McGraw Hill.
Wickham, H. (2014). Tidy data. Journal of Statistical Software, 59(10), 1-23. https://doi.org/10.18637/jss.v059.i10
The Purdue Global AC570 Unit 4 instructions
Unit 4 of AC570 asks you to profile a data population before testing it. State the scope: entities, period, row count and extract date. Check coverage at a fine level, such as days by location, because annual totals can hide gaps. Check completeness of each field later tests need. Describe the mix of key categories and whether it shifts over time. Tie totals to the general ledger by month, not only by year, since errors can offset. Examine distributions for impossible or unexpected values. For every gap you find, report it, size it, explain its cause if known and say what it affects, without repairing it silently. End with a verdict on whether the population is fit for testing and what exclusions or cautions later tests must apply. Ground the checks in the AICPA guide and Richardson and colleagues, with Wickham on table structure, in APA 7.
How this AC570 Unit 4 example is built
The sample's scope covers 31 facilities, fiscal 2025 and 413,896 rows. The coverage panel shades a facility-by-month grid and finds Facility 27 empty from March 3 to 9, with payments falling to 490 from 638 in February, traced to a terminal outage with paper receipts never keyed. Field completeness notes 214 blank reason codes and 41 electronic refunds without check numbers. The credit mix panel shows promotions at 44 percent and a June doubling of goodwill at Facility 22. The month-by-month tie finds only the December pass-through and Facility 27's March shortfall. The highlighted sentence states the verdict, and the closing excludes that facility-month from later tests.
Reading the AC570 Unit 4 grading rubric
Profiling exercises in AC570 earn points for finding problems that aggregate totals hide and for reporting them precisely. Graders check that coverage is examined at a fine grain, that field completeness is measured for the fields later tests use, and that the ledger tie is done by month. The rubric rewards sizing each gap, explaining its cause and stating what it affects. A clear verdict on fitness for testing, with specific exclusions, shows the profile was used. Exercises that report only summary statistics, tie totals once for the year or fix gaps without disclosure lose credit. Clear panels and APA 7 references to the guidance support the work.
Common AC570 Unit 4 mistakes, and how to avoid them
Common Unit 4 problems include profiling with averages and totals that cannot reveal a missing week. Others check completeness for every field but not the ones the tests need. The ledger is tied annually, so offsetting monthly errors pass unnoticed. Gaps are found and quietly filled or deleted, removing the evidence a reviewer needs. Shifts in category mix, such as a sudden rise in one credit type, are not noticed. The profile ends with statistics but no verdict. If your section's population differs, a writer can design the panels and verdict for your data.
Get an AC570 Unit 4 example written to your instructions
Send the prepared file from Unit 3, or whatever dataset your Unit 4 prompt supplies, together with the rubric and any control totals the case provides. The profile sheet, its coverage grid and a verdict on what the file can support arrive within 24-48h. A first custom sample is free of charge. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
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AC570 Unit 4 questions, answered
How is profiling different from descriptive statistics?
Descriptive work summarizes what the data says; profiling asks whether the data is all there and fit to say anything. The AC570 sample counts activity by facility and day, blank rates by field and ties by month before any average appears. A mean computed on a file missing a week at one site describes the file rather than the business, which is why this check runs first.
What should a profile do when it finds a gap?
Report it, size it and say what it affects, without repairing it silently. The sample names the seven missing days at Facility 27, estimates the payment shortfall they caused and recommends excluding that facility-month from modeling. If your data allows the missing records to be requested again, the profile can say so; either way the gap stays visible to the reader.
Why tie totals month by month instead of once for the year?
Because errors can offset. A month short by a few thousand dollars and another long by the same amount agree at year end and still misstate both months. Monthly ties in the sample match eleven months exactly and isolate December's 997.37 difference to one entry. Graders in AC570 often treat the monthly tie as evidence the population is understood, not merely counted.
Where can I find a free AC570 Unit 4 sample paper?
This page holds a full AC570 Unit 4 population profiling exercise for Stowfield Storage with a facility-day coverage grid, completeness, mix, a monthly ledger tie and a verdict, with APA 7 references.
Why would annual totals miss the seven-day gap?
Facility 27's March deposits were booked directly to cash, so its revenue looked close to plan. Only counting ledger activity day by day showed that a week of payments never entered the tenant ledger.