| Course | BU 451 Programming for Business Analytics |
|---|---|
| Unit | Unit 6 |
| Paper type | Analysis script with output |
| Length | About 930 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | BS in Business Analytics |
| Updated | September 2026 |
Free sample paper for BU 451 Unit 6
Three Tables and Two Figures, None Made by Hand: An Analysis Script With Output That Reads an Invented River Outfitter's Season by Site, Weather and Channel
Student Name
Business, Herzing University
BU 451: Programming for Business Analytics
Instructor Name
March 25, 2026
Three Tables and Two Figures, None Made by Hand: An Analysis Script With Output That Reads an Invented River Outfitter's Season by Site, Weather and Channel
What the Script Produces
Script 06_analyze.py is the first to answer questions for Riverbend Paddle Co., the invented Chattanooga kayak and paddleboard rental business this course follows. It reads the cleaned rentals and the combined site-day table built in the previous unit, and it writes three tables and two figures to the output folder. Every output in the submission was written by this code; nothing was copied, retyped or adjusted by hand, and each output carries a caption stating what it counts and over what period. The paper below presents the outputs as the script wrote them, with a short interpretation after each.
Sandve et al. (2013) advise keeping a record of how each result was produced and avoiding manual steps between the analysis and the report. The practical test is that deleting the output folder and rerunning the script recreates every table and figure exactly.
Table 1: The Season by Site
Caption written by the script: "Rentals, revenue, median rental duration and fleet utilization by launch site, April 1 to October 31, 2025. Utilization is rental hours divided by craft available times 10 open hours times 207 open days; each rental is counted as one craft."
| Site | Rentals | Revenue | Median duration (hours) | Craft | Utilization |
|---|---|---|---|---|---|
| CHA-1 | 8,210 | $402,300 | 2.5 | 34 | 31.5% |
| CHA-2 | 4,390 | $197,550 | 2.0 | 22 | 21.2% |
| CHA-3 | 6,019 | $294,900 | 3.0 | 30 | 31.0% |
| All sites | 18,619 | $894,750 | 2.5 | 86 | 28.7% |
CHA-1 is the busiest site by rentals and revenue, but CHA-3's longer rentals give it almost the same utilization. CHA-2 uses about a fifth of its fleet's available hours, which suggests it holds more craft than its demand needs. The utilization figure rests on an assumption stated in the caption, one craft per rental, which understates use when a family rents two kayaks on one ticket; the direction of the error is the same at every site, so the comparison between sites holds.
Table 2: Rentals and Weather
Caption written by the script: "Average rentals per open site-day by weather, 621 open site-days. Days with 0.25 inches of rain or more are grouped as rainy regardless of temperature; other days are grouped by daily high temperature."
| Weather group | Site-days | Total rentals | Average rentals per site-day |
|---|---|---|---|
| Rainy | 39 | 668 | 17.1 |
| Below 75 degrees | 94 | 1,786 | 19.0 |
| 75 to 84 degrees | 213 | 6,475 | 30.4 |
| 85 to 94 degrees | 231 | 8,432 | 36.5 |
| 95 degrees or above | 44 | 1,258 | 28.6 |
| All open site-days | 621 | 18,619 | 30.0 |
Rentals rise with temperature up to the mid-90s and then fall. The hottest days, 95 degrees or more, average fewer rentals than days in the upper 80s, which fits the manager's observation that people avoid the river in extreme heat. Rain cuts rentals roughly in half. These are associations in one season's data; they do not account for weekends, holidays or school vacations, which also vary with the season, so they should not be read as the effect of weather alone.
Table 3 and the Two Figures
Table 3 reports rentals and revenue by booking channel: 11,540 rentals and $583,100 online, 2,210 and $104,650 by phone, and 4,869 and $207,000 walk-up. Online bookings make up 62 percent of rentals and 65 percent of revenue, since online customers book longer rentals slightly more often.
Figure 1 is a line chart of weekly rentals by site across the 31 weeks of the season, written to output/fig1_weekly_rentals_by_site.png. It shows all three sites peaking in the week of July 4 and a second, smaller peak in late August, with CHA-2 flat compared with the others. Figure 2, output/fig2_rentals_by_weather.png, is a bar chart of Table 2's averages, with bars in the order of the weather groups rather than sorted by height, so the rise and fall with temperature can be seen. Both figures were drawn with the matplotlib library (Hunter, 2007), with titles, axis labels, units and a source line stating the data file and the date the script ran. Each figure's caption is written by the script into a text file beside the image, so the caption and the picture can never drift apart.
How the Script Checks Its Own Outputs
Before writing anything, the script compares its totals with figures established in earlier units, and stops if they disagree. Rentals in Table 1 must add to 18,619, the count of cleaned rentals; revenue must add to $894,750, the total confirmed when the site-day table was built; and site-days in Table 2 must add to 621, the number of open site-days. Each check prints a line such as "Check: Table 1 rentals match cleaned total (18,619)." These checks cost a few lines of code and protect against the most embarrassing kind of error, a table whose rows do not add up to the total printed beneath them. They also document the connections between units: a reader can see that Table 1 was built from the same records the cleaning script produced, not from a separate export pulled on a different day. If the owners replace the data with a corrected file, the checks will confirm that the new outputs still reconcile before any of them is saved.
What Was Deliberately Not Produced
The script does not produce a forecast, a model or a recommendation; those belong to later units and would need more than one season of data. It does not produce a revenue figure per customer, because customers are not identified across rentals in this data. And it produces no screenshot of anything. If a figure is wrong, the fix is in the code, and rerunning the script replaces the figure everywhere it appears. McKinney (2022) notes that the habit of saving outputs from code rather than copying them from an interactive session is what allows an analysis to be repeated and extended when new data arrive, and the owners already plan to add the 2026 season. Riverbend Paddle Co. and every figure in these outputs are composites for this course.
References
Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9(3), 90-95. https://doi.org/10.1109/MCSE.2007.55
McKinney, W. (2022). Python for data analysis: Data wrangling with pandas, NumPy, and Jupyter (3rd ed.). O'Reilly Media.
Sandve, G. K., Nekrutenko, A., Taylor, J., & Hovig, E. (2013). Ten simple rules for reproducible computational research. PLOS Computational Biology, 9(10), Article e1003285. https://doi.org/10.1371/journal.pcbi.1003285
BU 451 Unit 6 instructions, in plain terms
BU 451 Unit 6 asks students to write an analysis script that produces tables and figures. Requirements usually include generating every output from code, saving outputs to files, labeling each with a caption that says what it counts and over what period, and briefly interpreting the results. Many instructors ask whether screenshots are acceptable; they generally are not, because they cannot be regenerated. Interpretation should be short and should note limits. Figures should have titles, labeled axes and units. The submission typically includes the script, the output folder and an APA 7 write-up presenting each output with its caption and a short reading, plus a note on what the analysis does not attempt.
Inside the BU 451 Unit 6 example
The paper opens by stating what the script reads and writes and the rule that nothing is made by hand. Table 1 appears with its script-written caption, followed by an interpretation that names the utilization assumption and its likely effect. Table 2 follows with its caption and a reading that separates association from cause. A section describes Table 3 and the two figures, including why bars follow weather order and how captions are saved beside images. A section explains how the script reconciles its totals with earlier units before saving. The final section lists outputs deliberately not produced, such as forecasts and screenshots, and explains why.
Reading the BU 451 Unit 6 rubric
Rubrics for the analysis script generally reward outputs generated entirely by code, informative captions, clear figures, accurate figures and restrained interpretation, with presentation and APA. Code generation earns full credit when deleting and rerunning recreates every output. Captions score highest when they state what is counted, the period and any assumptions. Figures are judged on titles, axis labels, units and sensible ordering. Accuracy rewards totals that reconcile with earlier steps. Interpretation earns points when it is short, tied to the outputs and honest about limits such as confounding by season. Instructors often credit scripts that check their own totals before writing anything. Scripts that write each caption beside its figure also score well, since the explanation cannot drift from the image.
BU 451 Unit 6 help before you submit
Analysis scripts often lose points when some tables are typed into the report by hand, which breaks the link between code and results. Another common problem is outputs without captions, leaving readers to guess what a figure counts. Students frequently use default chart settings with unlabeled axes or bars sorted in a misleading order. Some interpret associations as causes, such as weather driving rentals without considering weekends and holidays. Others produce too many outputs, burying the main findings. Many never check that table totals match earlier counts. Finally, submitting a report built at work for this assignment raises confidentiality issues; rebuilding the analysis on course data shows the same skills.
Get a BU 451 Unit 6 example written to your instructions
Paste the assignment text, the rubric and any output format your BU 451 section fixes, together with the data and whatever you have already written. The custom example saves every table and figure from code, names the files by content, builds its own labels, captions each output by population and period, and clears the directory on each run. First one free, 24 to 48 hours.
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BU 451 Unit 6 questions, answered
Do I need to explain what the results mean?
Describe them, do not advise on them. Saying that a caption reports orders per region over a stated span is description and belongs here; saying which region the company should invest in is a recommendation and belongs to the analytics sequence rather than to this course. Where the instructions ask for commentary, keep it about what the output shows and how it was produced.
Are screenshots ever acceptable?
Rarely, and never as a substitute for the file itself. A picture of a chart the code saved is harmless; a picture standing in for output the code never wrote is the problem, because nothing regenerates it. If your section requires images inside a document, generate the images from the script and place them, rather than capturing a screen.
I built a report at work that does exactly this. Can I submit it?
No, because the output carries the organization's numbers on its face. A chart made from internal figures shows volumes, customers or revenue that the company has not agreed to share with a school, and removing the labels does not remove the values. Build the graded artifact from the unit's dataset; a report you produced on the job stays inside the job.
Where can I find a free BU 451 Unit 6 sample paper?
This page carries the whole BU 451 Unit 6 analysis script with output for free, including all three tables, the figure descriptions and margin notes. If your data or questions differ, we can build a parallel set of outputs around your prompt for free, typically within 48 hours.
Are screenshots acceptable in BU 451 Unit 6?
Generally not. The sample writes every table and figure to a file from code, so rerunning the script recreates them exactly, which a screenshot cannot do.