Two composite counties, one calculation each: the Week 3 rate exercise in PUBH 1000, worked through with denominators labeled and the per 100,000 multiplier stated aloud. Searches like "pubh 1000 week 3 assignment example", "pubh1000 week 3 sample" and "pubh 1000 week 3 example" land here.
What a finished PUBH 1000 Week 3 rate exercise looks like
The exercise runs on a four-column table. County A records 180 newly diagnosed cases against a population of 42,000; County B records 240 against 96,000. Both crude rates are computed on the page, 428.6 and 250.0 per 100,000, with the multiplication shown rather than asserted. A paragraph underneath states the comparison in one sentence and then explains it: the second county has more people to spread its cases across. Two data sources are named where they belong, CDC WONDER for the case counts and the Census Bureau county population estimates for the denominators, along with the year both were pulled for. A final short paragraph names age adjustment as a method that exists, says why it would matter if the two counties differed in age, and does not attempt it.
How a PUBH 1000 Week 3 example is structured
The page runs in calculation order rather than in essay order. A two-sentence setup states what is being compared and why raw counts will not do it. The table follows, with columns for cases, population, calculation and result, so that the middle column carries the work instead of a footnote. Each row is then restated in prose as a full sentence, because a rate quoted without its denominator and its year is not yet a claim. The comparison paragraph comes next and is deliberately short. Sources appear immediately after the numbers they produced, not gathered at the end, and the reference list repeats them formally. The age adjustment paragraph closes the exercise, marked as a limitation rather than as an extension of the analysis.
Counts first, on purpose
Both raw counts appear before either rate does, so the reversal at the end has something to reverse.
The calculation column
180 divided by 42,000, then multiplied by 100,000. The middle column carries that arithmetic openly instead of hiding it behind a rounded answer.
Every rate said as a sentence
Each result is written out with its population, its year and its unit attached, which is what turns a number into something a reader can check.
Why more cases can mean less risk
One paragraph, four sentences. The denominator does the explaining, and no other cause is offered where arithmetic already accounts for the gap.
Age adjustment, named not done
The closing note says what age adjustment corrects and why two counties with different age profiles would need it before any stronger claim gets made.
Where marks go in PUBH 1000 Week 3
Arithmetic accuracy is scored plainly, and a misplaced decimal costs more here than a thin paragraph does. Past that, the points sit in labeling. A rate written without a unit, or with the multiplier left unstated, tends to be marked down even when the number is right, since 428.6 means nothing on its own. Rubrics in many sections carry a line about interpretation, and the safe target there is one clean explanatory sentence about the denominator rather than three speculative ones about diet or access. Naming both data sources with a year attached usually earns its own credit. Graders also watch for the count and rate vocabulary staying separate throughout, because a paper that calls 240 cases a high rate has undone the exercise in its own summary.
Get a PUBH 1000 Week 3 example written to your instructions
Forward the Week 3 prompt with the rubric your classroom posted and any figures the assignment supplies, and a worked exercise comes back using those figures. The first sample is free and lands within 24-48 hours. Numbers from your own state or county can stand in for the composites, and the arithmetic gets shown either way.
PUBH 1000 Week 3 questions, answered
Are the two counties in the exercise real places?
They are not. Both were built to make one arithmetic point cleanly, which real county data rarely does without a page of caveats about reporting differences. The sources named in the sample, CDC WONDER and the Census Bureau population estimates, are the ones an actual version would draw on, and the desk can build the exercise from live figures if your prompt asks for them.
Why per 100,000 and not per 1,000?
Because the condition in the example is uncommon enough that per 1,000 would push both results below one and make them awkward to compare. The multiplier is a presentation choice, and the sample says so in the setup. Where a section fixes the multiplier in the prompt, the sample uses that one and keeps the calculation column visible regardless.
Does the exercise need age adjustment?
Not usually at this level, and the sample is explicit that it has not performed one. What earns credit in the third week is knowing that age adjustment exists, naming what it corrects for, and saying why two populations of different ages cannot be compared on crude rates alone. Attempting it badly costs more than leaving it named and undone.