Sales and freight-out, tracked across twenty-four months, expose a December cutoff gap: the core finding of an AC312 Unit 5 ledger relationship analysis. Searches like "ac 312 unit 5 assignment example", "ac312 unit 5 sample" and "ac312 unit 5 example" land here.
What a finished AC312 Unit 5 ledger relationship analysis looks like
A monthly table, a scatter plot with a fitted line, a residual chart and three paragraphs of findings. The table lists sales and freight-out for each month of fiscal 2024 and 2025, with freight as a percentage of sales beside them; twenty-three of the months fall between 3.5 and 4.1 percent. The scatter shows the relationship directly, with a correlation of 0.97 once December 2025 is set aside and a slope of about 3.7 cents of freight per sales dollar. The residual chart plots each month's distance from the line, and one bar stands far below the rest: December 2025, with 97,700 booked against roughly 160,600 expected, more than six standard deviations short. The findings name that month, state the likely cause and say what evidence would confirm it.
How a AC312 Unit 5 example is structured
The analysis states its hypothesis before any figure: freight-out should rise and fall with sales, because the company ships what it sells. Next comes the table, so every monthly figure is visible before it is summarized. The scatter and the correlation come next, and the analysis explains why December 2025 was excluded when fitting the line, since including a suspected error would bend the expectation toward it. Both correlations are reported so the choice stays transparent. The residual chart then carries the finding. The first findings paragraph describes the relationship; the second isolates the December gap and proposes the likely cause, carrier invoices for December deliveries arriving in January and never accrued; the third names the confirming test, a trace of January carrier invoices by delivery date, and the account at stake, accrued liabilities.
A stated hypothesis
Freight-out should follow sales because the company ships what it sells. The expectation is written down before anything is computed, so the data can contradict it.
Twenty-four months in one table
Sales, freight-out and their ratio for each month. Twenty-three months fall between 3.5 and 4.1 percent; one does not.
The fitted line
Correlation of 0.97 and a slope near 3.7 cents per sales dollar, with December 2025 set aside and the reason for setting it aside stated.
The month off the line
December 2025 booked 97,700 of freight against about 160,600 expected, a residual more than six standard deviations below the rest.
Cause and confirming test
Carrier invoices for December deliveries likely arrived in January without an accrual. Tracing them by delivery date would confirm it, and accrued liabilities would move.
Where marks go in AC312 Unit 5
The deepest cut goes to an analysis that reports a correlation and stops, because the course grades whether a relationship leads somewhere in the accounts. A strong coefficient with no residual review misses the one month that matters. Graders next check whether the exclusion of December 2025 from the fitted line was explained; excluding a point without a stated reason looks like tuning the result. Claiming the relationship proves an error, rather than pointing to a month that needs evidence, overstates what a correlation can show. Unlabeled axes or missing units lose presentation marks. Findings that name the anomaly without the account it affects, accrued liabilities and freight expense understated at year end, lose the consequence marks many rubrics weight most heavily.
Get a AC312 Unit 5 example written to your instructions
Name the two accounts your Unit 5 prompt pairs, or the ones your dataset allows, and send the monthly figures with the rubric. The table, fitted line, residual chart and findings return within 24-48h, with the calculation file attached so each figure can be checked. The first custom sample is free, whichever pair you choose.
AC312 Unit 5 questions, answered
Why exclude the suspicious month when fitting the line?
Because the line is meant to represent normal behavior, and a month suspected of an error would pull the expectation toward itself, shrinking the very gap being examined. The AC312 sample fits the line on the other twenty-three months, reports the correlation both ways, 0.97 without December and 0.95 with it, and explains the choice so a reader can judge it.
Does a high correlation mean one account causes the other?
No. It shows that the two move together, which is enough to build an expectation and spot a departure from it. Here the causal story is plausible, since goods sold must be shipped, but the analysis does not rely on it. A strong correlation between two accounts with no business link would be treated as coincidence and never used as an expectation.
Which two accounts should the analysis compare?
Whichever pair the prompt names, or, if left open, a pair with a clear business reason to move together: sales and receivables, payroll and headcount, purchases and inventory. The AC312 sample uses sales and freight-out because the link is intuitive and a cutoff error shows clearly. The pairing is stated and justified in the first paragraph.