PUBH 8033 Week 9 Table and Figure Audit Example

Course	PUBH 8033 Interpretation and Application of Public Health Data
Week	Week 9
Paper type	Table and figure audit brief
Length	About 630 words, 5 pages
Format	APA 7 student paper
School	Walden University
Program	PhD in Public Health
Updated	October 2026

Free sample paper for PUBH 8033 Week 9

Could a Reader Confirm a Single Number? A Table and Figure Audit of a Composite County Older Driver Class's Annual Report, Recording Every Missing Denominator, Undefined Term and Distorted Axis

Student Name

Walden University

PUBH 8033: Interpretation and Application of Public Health Data

Instructor Name

Month Day, Year

What this page is doingThe title sets the audit's test, whether a reader with only the report could check any figure in it, which most public reports fail.

Could a Reader Confirm a Single Number? A Table and Figure Audit of a Composite County Older Driver Class's Annual Report, Recording Every Missing Denominator, Undefined Term and Distorted Axis

The Report and the Test

Larkin County's aging services department published an annual report on its Safe Driving After 70 program with two tables and three charts. This audit asks one question of every display: could a reader holding only this report confirm a single number in it? Where a number can be recomputed from other numbers in the report, the audit recomputes it. Where it cannot, the audit records why. The report and its figures are composite.

What this page is doingStating one test for every display makes the audit consistent and easy to follow.

Table 1: Participants by Enrollment Site

The table lists participants at senior centers, libraries and the licensing office, with percentages. The percentages add to 100, and recomputing them from the counts confirms them. But the table never says whether "participants" means applicants, enrollees or completers, and the total, 412, matches completers only. A reader comparing it with the 730 applicants mentioned in the text would be confused. Finding: undefined term.

Table 2: Crashes Before and After the Class

The table reports "crash rate before" and "crash rate after" for completers: 6.1 and 4.6. No denominator is given, and no time period is stated for "before." A reader cannot tell whether the rates are per 100 drivers, per 10,000 miles or per year, or whether the before period was one year or three. The table also omits the waitlisted comparison group entirely, so the drop from 6.1 to 4.6 could reflect regression to the mean: people who enroll after a bad year tend to have a better next year anyway. Findings: missing denominator, missing period, missing comparison.

Chart 1: Satisfaction Ratings

A bar chart shows that 94% of completers rated the class "good" or "excellent." The number of respondents is missing. If only half of completers returned the form, the 94% describes a self-selected subset. Finding: missing denominator.

Chart 2: Crash Rates, Completers Versus Waitlisted

A bar chart compares crash rates of 4.6 and 5.7 per 100. The vertical axis begins at 4.0, not zero, so the waitlisted bar appears more than twice as tall as the completers' bar, although the true ratio is 0.81. No confidence intervals are shown. Finding: distorted axis; missing uncertainty.

Chart 3: Self-Reported Driving Changes

A pie chart shows that 61% of completers said they "drive more carefully now." There is no comparison with waitlisted applicants, and the question wording is not given. Finding: undefined measure; no comparison.

Table 1

Audit Summary

Display	Could a reader confirm a number?	Main problem \|
Table 1	Yes, percentages	"Participants" undefined \|
Table 2	No	No denominator, period or comparison \|
Chart 1	No	Number of respondents missing \|
Chart 2	Partly, values only	Axis starts at 4.0; no intervals \|
Chart 3	No	Question wording and comparison missing \|

Note. Audit prepared for this course.

What the Report Should Add

Every rate needs its numerator, denominator and period. Every comparison should include the comparison group and an interval. Axes on bar charts should start at zero. Terms such as "participant" should be defined once. And self-reported outcomes should give the question asked. A report that claims the class makes people safer should also say how its result compares with published reviews, which have found classroom education alone unlikely to reduce crashes (Korner-Bitensky et al., 2009). Earlier evaluations of driver education programs have shown that attendees can differ from nonattendees before the class (Nasvadi & Vavrik, 2007), so a before-and-after table without a comparison invites exactly the misreading this report encourages. Trials that report both per-person and per-mile rates with intervals, such as one evaluating safety education for high-risk older drivers (Owsley et al., 2004), offer a model of transparent reporting.

References

Korner-Bitensky, N., Kua, A., von Zweck, C., & Van Benthem, K. (2009). Older driver retraining: An updated systematic review of evidence of effectiveness. Journal of Safety Research, 40(2), 105-111. https://doi.org/10.1016/j.jsr.2009.02.002

Nasvadi, G. E., & Vavrik, J. (2007). Crash risk of older drivers after attending a mature driver education program. Accident Analysis & Prevention, 39(6), 1073-1079. https://doi.org/10.1016/j.aap.2007.02.005

Owsley, C., McGwin, G., Phillips, J. M., McNeal, S. F., & Stalvey, B. T. (2004). Impact of an educational program on the safety of high-risk, visually impaired, older drivers. American Journal of Preventive Medicine, 26(3), 222-229. https://doi.org/10.1016/j.amepre.2003.12.005

PUBH 8033 Week 9 instructions, in plain terms

Table and figure audit assignments ask students to examine data displays in a report and judge whether they are accurate, complete and interpretable. Prompts often require checking each display for denominators, time periods, definitions, comparison groups, uncertainty and visual distortion, recomputing figures where possible and recommending corrections. Instructors reward audits that apply one clear test consistently, distinguish errors from omissions, explain how each problem could mislead a reader and propose specific fixes rather than general calls for clarity. Some instructors supply the report; others ask students to find a public report from their own agency.

How this PUBH 8033 Week 9 example is built

The brief states the test and applies it to each display in order. Each display is handled in turn, noting its content, what can be recomputed and what problem was found, labeled as a finding. A summary table lists all five displays with whether a number could be confirmed and the main problem. A closing section lists what the report should add, citing evidence on self-selection in driver courses, transparent reporting in a randomized trial and a review of retraining programs. Every finding is labeled with a short category, such as missing denominator or distorted axis, which makes the summary table easy to build. The fixes are written as instructions an analyst could follow.

PUBH 8033 Week 9 rubric: what earns full marks

Graders look for consistent application of a test, accurate identification of problems and useful recommendations. Recomputing figures where possible demonstrates rigor. Explaining how a problem would mislead, for example how a truncated axis exaggerates a difference, shows understanding. Specific fixes earn more than general advice. Connecting reporting problems to known biases, such as regression to the mean in before-and-after data, adds depth. Audits that recompute numbers where possible show more rigor than audits that only describe displays. Explaining how a missing comparison invites regression to the mean connects reporting to bias. Graders reward specific, actionable fixes and a summary table that lets a reader see every problem at once. Audits that rank problems by how badly each could mislead a reader help authors fix the worst first. Graders also reward audits that suggest revised captions or axis labels in exact words.

Common PUBH 8033 Week 9 mistakes, and how to avoid them

Students often comment on design taste rather than information. For each display, ask what number it reports, out of what, over what period and compared with what. Try to recompute it. Check axes on bar charts. Look for missing respondent counts. Write the fix in one line. A draft built on your own data can be arranged. Use the same questions for every display so nothing is missed. Recompute any percentage or rate you can. Measure where bar chart axes start. Note whether intervals are shown. Keep each finding to one line in the summary. Send findings to the report's authors before publishing the audit.

Get a PUBH 8033 Week 9 example written to your instructions

Enclose the Week 9 prompt, rubric and the report, article or displays your section assigned for audit. An audit table testing whether each number can be traced, with recomputations, annotated displays and repairs, lands in 24-48h at zero cost on the first. The annual report it audits is a made-up example; the defects in your assigned displays have to be found in them directly.

More PUBH 8033 papers and PhD in Public Health samples

PUBH 8033 Week 9 questions, answered

Where can I find a free PUBH 8033 Week 9 sample paper?

The full Week 9 audit is reproduced above, checking every table and chart in a driver class's annual report.

What is the test applied to each display?

Whether a reader with only the report could confirm a single number in it.

What was wrong with the before-and-after crash table?

It gave no denominator, period or comparison group, inviting a misreading driven by regression to the mean.

Why does a bar chart axis starting at 4.0 mislead?

It makes a crash rate ratio of 0.81 look like one group had more than twice the other's rate.

What should every rate in a report include?

Its numerator, denominator and period, with a comparison group and an interval where relevant.