| Course | BU 454 Data Visualization |
|---|---|
| Unit | Unit 8 |
| Paper type | Visual report with rationale |
| Length | About 1,000 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | BS in Business Analytics |
| Updated | September 2026 |
Free sample paper for BU 454 Unit 8
The Season in Four Charts, Each With the Version We Threw Away: A Visual Report With Rationale for the Owners of a Composite Montana Ski Area
Student Name
Business, Herzing University
BU 454: Data Visualization
Instructor Name
April 22, 2026
The Season in Four Charts, Each With the Version We Threw Away: A Visual Report With Rationale for the Owners of a Composite Montana Ski Area
Purpose and Audience
This report tells the owners of Bearpaw Ridge, a composite ski area in western Montana built for this course, what happened in the 2024 to 2025 season and what it suggests for the next one. It uses four charts, chosen from the many made this term, because the owners will read it in about ten minutes before their spring meeting. Each chart carries a short rationale: the comparison it serves, the visual channel that carries that comparison, and the alternative that was tried and dropped. Knaflic (2015) argues that a report should show only the charts the audience needs to reach a conclusion and should say plainly what each is meant to show; the rationale notes serve any owner curious about why a chart was drawn the way it was.
The season in brief: 128,400 skier visits over 114 open days, $894,000 in lift revenue across all ticket types, two closures, and a smoothed daily level that was weakest in January, not in February as the owners had feared.
How the Four Charts Were Chosen
More than twenty charts were made during the term, and most are not in this report. The four were chosen by listing the decisions the owners face at their spring meeting and keeping one chart for each: whether the season's pattern calls for marketing effort in particular weeks, how to set base staffing, where to add weekend staff and how to price next season's passes. Charts that informed the analysis but not a decision, such as the histogram of daily visits and the scatter of snowfall against weekday crowds, were left in an appendix the owners can open if they want the detail. The ticket-type chart was cut after a draft review, because the owners already knew the pass share and it changed nothing. Each chart that remains ends with the recommendation it supports, so the report can be read as four short arguments rather than a gallery. The order follows the meeting's agenda, not the order in which the charts were made during the term.
Chart 1: How the Season Moved
The chart shows a seven-day rolling average of daily visits from December 12 to April 6 on an axis starting at zero, with the Christmas to New Year period, Presidents' Day weekend and spring break labeled directly. The season's level rose to about 2,700 a day at the holidays, fell to about 1,000 through January, rose to about 1,350 in February and held near 1,200 in March.
Comparison served: the level of demand over time. Channel: position along a common vertical scale, joined as a line. Alternative dropped: monthly totals as bars. The bars were simpler, but they buried the January weakness inside a December total inflated by the holidays and hid the timing of the February rise, which came in one storm week. The line makes both visible.
Chart 2: What a Typical Day Looks Like
Three box plots on one axis show daily visits for weekdays, weekend days and holidays: medians of 690, 1,790 and 2,480.
Comparison served: the spread of visits within each type of day. Channel: position of the box, median line and whiskers on a common scale. Alternative dropped: the season average of 1,126 visits a day, which the owners had used for staffing. No type of day resembles it, and staffing to it leaves weekends short and weekdays overstaffed. The chart supports the report's first recommendation: set base staffing separately for weekdays and weekends.
Chart 3: Which Lifts Gain Most on Weekends
A dot plot shows weekday and weekend average rides for each of the nine lifts, sorted by the ratio between them, with circles for weekdays and triangles for weekends. The beginner carpet more than triples on weekends; the backside lift barely changes.
Comparison served: the change within each lift from weekday to weekend. Channel: position of two marks on a shared scale, joined by a line. Alternative dropped: grouped bars, which invited readers to compare lifts with one another rather than each lift with itself, and led the owners' staff to name the biggest lift instead of the biggest gainer. The chart supports the second recommendation: add a lesson instructor and a carpet attendant on weekends, not more staff on the main lifts.
Chart 4: Season Passes, Honestly Drawn
Two small panels show season passes sold over five seasons, from 1,905 to 2,040, as flat columns from zero, and pass revenue over the same seasons, which grew about 2.7 percent as discounts deepened.
Comparison served: growth in the pass program by volume and by money. Channel: length from a zero baseline. Alternative dropped: the marketing slide's three-dimensional columns on an axis starting at 1,880, which made a 7 percent rise look six times larger. The honest version shows steady but modest growth and a revenue line that argues against deeper early-purchase discounts. It supports the third recommendation: hold next season's early pass price rather than cutting it again.
What the Report Does Not Claim
The four charts describe one season. They do not forecast next season, and they do not prove causes; the relationship between snowfall and weekday crowds, for example, rests on only nine big-snow days. All charts meet the accessibility rules adopted in the color unit: no information is carried by color alone, every mark meets the contrast standard, and each chart was checked in grayscale. Each is labeled directly, without legends. Tufte (2001) urges designers to show the data and let the reader think about substance rather than decoration, and every alternative dropped in this report was dropped because it asked the reader to decode the picture before seeing the season. Cleveland and McGill (1984) supply the principle behind every channel chosen: values the owners must compare are placed on a common scale. Bearpaw Ridge and all of its figures are invented for the course.
References
Cleveland, W. S., & McGill, R. (1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79(387), 531-554. https://doi.org/10.1080/01621459.1984.10478080
Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. Wiley.
Tufte, E. R. (2001). The visual display of quantitative information (2nd ed.). Graphics Press.
BU 454 Unit 8 instructions, in plain terms
The final BU 454 unit asks students to assemble a short visual report with a written rationale for each chart. Common requirements include a small number of charts chosen for the audience, a statement for each of the comparison it serves and the visual channel used, the alternatives considered and why they were rejected, and conclusions or recommendations supported by the charts. Many instructors ask how many charts to include and whether earlier work may be reused; reuse is expected, and fewer well-chosen charts score better than many. Turning charts made at work into the report is discouraged. The report is usually brief, written in APA 7, with each chart described or embedded.
How this BU 454 Unit 8 example is built
The report opens with its audience, purpose and a brief summary of the season. A section explains how four charts were chosen from more than twenty by matching one to each decision the owners face. Each chart then has its own section describing what it shows, followed by the comparison served, the channel and the alternative dropped, and ending with the recommendation it supports. The four cover the season's level, typical days by type, weekend gains by lift and pass sales with revenue. A closing section states what the report does not claim, confirms accessibility checks and ties every channel choice to the principle of a common scale.
Where the points sit in the BU 454 Unit 8 rubric
Visual report rubrics at Herzing generally reward a focused selection of charts, a complete rationale for each, sound encoding choices, conclusions supported by the charts and honest limits, together with writing and sources. Selection earns full credit when each chart serves a decision the audience faces. Rationale scores highest when it names the comparison, the channel and a rejected alternative with a reason. Encoding choices are judged against perception research and accessibility standards. Conclusions reward recommendations that follow directly from specific charts. Limits earn points when the report says what the data cannot prove. Instructors also credit reports that move supporting detail to an appendix rather than crowding the main text.
BU 454 Unit 8 help: mistakes that cost points
Visual reports often lose points by including every chart made during the term, burying the few that matter. Another common problem is presenting charts without saying what each is meant to show. Students frequently describe encoding choices in general terms without naming the rejected alternative. Some draw conclusions the charts do not support, such as forecasts from one season. Others reuse earlier charts without updating them for accessibility. Many put charts in the order they were made rather than in the order the audience needs. Finally, basing the report on charts built at work can disclose internal results; rebuilding them on course data keeps the focus on design.
Get a BU 454 Unit 8 example written to your instructions
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BU 454 Unit 8 questions, answered
How many charts should the report carry?
Fewer than feels generous, because every one has to earn a defended rationale entry and a thin defense drags the whole submission down. Three or four is a common shape at this level unless the instructions set a number. If a chart cannot be tied to a question in the prose and an alternative in the rationale, it is decoration and cutting it raises the grade.
Can I reuse charts I made in earlier units?
Often yes, and sections that build toward this deliverable expect it, but check the instructions before assuming. Reused charts still need a rationale entry written for this report, since the comparison they were serving in an earlier unit may not be the one the argument needs now. Bring them into line with the conventions you settled on, rather than leaving three different color schemes on the page.
Could I turn the charts I make at work into this report?
The visuals you produce on the job are the employer's work product and they carry production figures, so they stay where they were built. What you can carry across is the judgment. Rebuild the argument on the assignment data and the rationale entries will read stronger than a classmate's, because you have watched real readers misread a chart and know which decision caused it.
Where can I find a free BU 454 Unit 8 sample paper?
The complete BU 454 Unit 8 visual report with rationale is free to read here, with all four charts, their dropped alternatives and margin notes. If your data or audience differ, tell us and a custom report is assembled free, typically within 48 hours.
How many charts should the BU 454 Unit 8 report carry?
As few as the audience's decisions need. The sample uses four, one per decision at the owners' meeting, and moves supporting charts such as the snowfall scatter to an appendix.