| Course | BU 454 Data Visualization |
|---|---|
| Unit | Unit 3 |
| Paper type | Comparison and ranking charts |
| Length | About 1,010 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 3
Sorted by the Number, Not the Name: Four Comparison and Ranking Charts for a Composite Montana Ski Area, With the One Place Where Size Order Gives Way
Student Name
Business, Herzing University
BU 454: Data Visualization
Instructor Name
February 11, 2026
Sorted by the Number, Not the Name: Four Comparison and Ranking Charts for a Composite Montana Ski Area, With the One Place Where Size Order Gives Way
What the Chart Set Must Do
The general manager of Bearpaw Ridge, the composite Montana ski area this course follows, asked for charts that let the owners rank and compare things at a glance: which lifts are busiest, which gain most on weekends, which ticket types bring in the most per visit and which trails skiers use most. A ranking chart succeeds when a reader can put the categories in order without effort. This unit builds four charts that put magnitude on position or length, sorts each by value unless the categories have a natural order, and defends every choice in a note.
Few (2012) recommends bar charts for comparing values across categories because lengths from a common baseline are compared accurately, and he advises sorting bars by value when the goal is ranking, since an alphabetical or arbitrary order forces the reader to do the sorting mentally. The 2024 to 2025 season data are composites.
Chart 1: Average Daily Rides by Lift
Form: horizontal bars, one per lift, sorted from most to fewest rides, with each bar labeled with its value. Length from a shared baseline is among the channels viewers judge most accurately (Cleveland & McGill, 1984), which matters here because the middle lifts differ by only a few hundred rides. Horizontal orientation leaves room for lift names without rotating text. The Summit Quad leads with 2,850 rides a day and the Upper Ridge surface lift trails with 310.
Note on the choice: sorting by value puts the answer to the question which lifts are busiest in reading order. The lift map order, which staff know by heart, was tried and rejected; it scattered the busiest lifts across the chart and made the manager's own eye jump back and forth.
Chart 2: Which Lifts Gain Most on Weekends
Form: a dot plot with two dots per lift, weekday and weekend average rides, joined by a thin line, sorted by the weekend-to-weekday ratio rather than by size.
| Lift | Weekday rides | Weekend rides | Weekend to weekday ratio |
|---|---|---|---|
| Carpet (beginner) | 640 | 1,970 | 3.1 |
| Ridge Triple | 1,290 | 2,940 | 2.3 |
| Aspen Double | 520 | 1,110 | 2.1 |
| Summit Quad | 1,980 | 4,120 | 2.1 |
| Bear Chair | 1,650 | 3,520 | 2.1 |
| Meadow Double | 1,050 | 1,960 | 1.9 |
| Timber T-bar | 700 | 1,170 | 1.7 |
| Upper Ridge Poma | 260 | 390 | 1.5 |
| Backside Double | 470 | 650 | 1.4 |
Note on the choice: the question here is not which lift is busiest but which gains most on weekends, so the sort is by the ratio. That reveals what a size-sorted chart hides: the small beginner carpet more than triples on weekends, when lesson groups arrive, while the backside lift barely changes. A grouped bar chart was tried; it showed the same values but the eye compared bars across lifts rather than within each lift, which is the comparison that matters here. The connecting line in the dot plot draws the eye along each lift's own change.
Chart 3: Revenue per Visit by Ticket Type
Form: horizontal bars sorted by value, with a vertical reference line at the all-visit average of $41. Lesson packages bring in $112 per visit, window day tickets $89, online day tickets $74, season passes about $10 per visit once a pass's price is spread over its holder's visits, and complimentary tickets nothing.
Note on the choice: the reference line lets a reader see at once which types sit above and below the average without reading numbers. The season pass bar is labeled with a short note, spread over an average of 46 visits, because a reader seeing $10 might otherwise conclude passes are unprofitable, when they supply committed revenue before the season starts.
Chart 4: The Ten Most-Skied Trails, and the Other Twenty-Four
Form: horizontal bars for the ten trails with the most gate scans, sorted by value, and a final bar in a lighter tone for the remaining 24 trails combined. Thirty-four bars would fit on a page but would bury the ranking the owners want; the top ten account for 61 percent of scans, which the combined bar makes visible.
Note on the choice: this chart shows where the size order gives way. Within the top ten, bars are sorted by scans. But the combined bar is always placed last, regardless of its size, because it is a different kind of category, a remainder, and putting it in size order would place it first and make it look like the most popular trail. Categories with a natural order, such as days of the week or trail difficulty, would likewise keep that order, since the order itself carries meaning.
How the Charts Were Checked
Each chart was checked by asking a staff member who had not seen the data to answer its question aloud, then timing the answer. For Chart 1, the question was which three lifts are busiest; for Chart 2, which lift gains most on weekends; for Chart 3, which ticket types bring in more than the average visit; and for Chart 4, what share of use the top ten trails carry. Every answer was correct within a few seconds. The rejected versions were checked the same way: with the lift-map order, the same person took about three times as long to name the three busiest lifts, and with a grouped bar chart for weekends, they named the Summit Quad, the biggest lift, rather than the beginner carpet, the biggest gainer. These small checks are not an experiment, but they confirm that each chart answers the question it was built for, which is the standard the owners will apply when they see it.
Choices Shared by All Four Charts
All four charts start their bars at zero, label values directly rather than relying on gridlines, and use one color except for a single highlight, the Summit Quad in Chart 1, which the manager wanted the owners to notice. Munzner (2014) advises spending the strongest visual channel on the attribute that answers the question and using color sparingly for emphasis, and the set follows that advice. None uses a legend: where two series appear, in Chart 2, they are labeled at the first lift's dots, so the reader never looks away from the data to decode it. Bearpaw Ridge and all of its numbers 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
Few, S. (2012). Show me the numbers: Designing tables and graphs to enlighten (2nd ed.). Analytics Press.
Munzner, T. (2014). Visualization analysis and design. CRC Press.
Reading the BU 454 Unit 3 instructions
BU 454 Unit 3 asks students to design charts for comparing and ranking categories. Typical requirements are a small set of charts using position or length for magnitude, sorting by value unless a natural order exists, a justification for each choice, and attention to how many categories one chart can hold. Many instructors ask when sorting by something other than size is appropriate; natural orders such as weekdays or difficulty levels, and remainder categories, are the usual exceptions. Charting your own team's figures is discouraged; the supplied data serve better. The deliverable is usually several charts with short notes, set out in APA 7, and strong answers describe the rejected alternatives as well.
How the BU 454 Unit 3 example is put together
The paper opens with the owners' four ranking questions and the case for sorted bars. Chart 1 sorts lifts by rides and explains why the lift map order was rejected. Chart 2 sorts lifts by weekend-to-weekday ratio, with a data table, and explains why a dot plot beats grouped bars for within-lift change. Chart 3 adds a reference line at the average revenue per visit and annotates the season pass bar. Chart 4 shows the top ten trails with a combined remainder placed last and explains why. A section describes choices shared by all four charts, and another reports quick staff tests of each chart and its rejected version.
BU 454 Unit 3 rubric: what full points look like
Rubrics for ranking charts usually reward appropriate channels, sensible sorting, justified exceptions, manageable category counts and clear notes, together with writing and APA. Channel choice earns full credit when magnitude is shown by position or length from a common baseline. Sorting scores highest when it follows the question, by value for ranking or by a ratio when change is the point. Exceptions are judged on whether natural orders and remainder categories are handled deliberately. Category counts reward grouping long tails rather than crowding a chart. Notes earn points when they explain the choice and the rejected alternative. Instructors also credit direct labeling instead of legends, which keeps the reader's eye on the data.
BU 454 Unit 3 help before you submit
Ranking charts commonly lose points by sorting categories alphabetically or in database order, forcing readers to rank them mentally. Another frequent problem is showing dozens of categories in one chart, hiding the ranking the audience wants. Students often sort a remainder category by its size, making other look like the leader. Some use vertical bars with rotated labels that are hard to read. Others rely on color legends where direct labels would be clearer. Many forget that the right sort depends on the question, such as ranking by change rather than size. Finally, charting a team's own numbers for coursework may expose colleagues' performance; supplied data avoid that problem.
Get a BU 454 Unit 3 example written to your instructions
Forward the Unit 3 instructions along with your BU 454 rubric and whatever data file or case the assignment names. We write a custom example that sorts by value, picks orientation from the labels, holds the zero baseline, chooses grouped over stacked where the comparison demands it and defends each decision. First custom sample free, back in 24 to 48 hours.
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BU 454 Unit 3 questions, answered
How many categories can one chart hold?
As many as can carry a readable label at the size the document renders, and that is usually fewer than the file offers. Where the list runs long, a common answer is to show the top group and collect the remainder into a single labeled band, then say in the note what was collapsed and why. Silently dropping categories is a different thing and reads as selection.
Is there ever a reason to sort by something other than size?
Yes, and saying which you chose earns the credit either way. An ordered category such as a size band or a rating scale keeps its natural sequence, because scrambling it destroys information the labels carry. A ranking question sorts by value. What loses marks is an order nobody chose, inherited from whatever sequence the rows happened to sit in.
Can I chart my own team's numbers instead of the supplied data?
The performance figures your team reports are the employer's records, and a graded assignment travels outside the building, so keep them out. If the assignment leaves the data open, published statistics from a government series or an industry body give you real variation to rank without the exposure. Charts built from figures you construct are fine too, provided you label them as case material.
Where can I find a free BU 454 Unit 3 sample paper?
A full BU 454 Unit 3 comparison and ranking charts example can be read here at no charge, with all four charts, their notes and margin notes. For your own categories, forward the prompt and we build a custom chart set for you free, generally within two days.
When should BU 454 Unit 3 sort by something other than size?
When the categories have a natural order, such as weekdays or difficulty, or when one is a remainder. The sample keeps a combined other-trails bar last so it is not mistaken for the most popular trail.