A monthly quality report showing a documentation compliance rate climbing from the sixties to the eighties looks like proof until you notice the denominator changed halfway through, and NR-559 Week 5 exists to build that reflex. This stage asks you to read a results section for what it actually establishes: what was compared, how large the difference was in units a clinician recognizes, how precisely it was estimated, and what the authors then claimed on top of it. Your section may print this as NR 559 or NR559; it is the same course. Chamberlain publishes no syllabi outside Canvas. The placement here is our teaching judgment from the course's catalog arc; your section's rubric decides what your week actually asks.
What NR-559 Week 5 asks for
The territory is interpretation, and the fear that surrounds it is mostly misplaced. Graduate nursing students are not asked to reproduce an analysis. They are asked to say, in plain language, what a result means and what it does not. That is a writing skill more than a statistical one, and the students who do it well are usually the ones who stopped trying to sound like statisticians.
Four questions carry almost every results paragraph you will ever need to write. What two things were compared? Which direction did the difference run? How large was it, expressed in something real such as minutes, points on a scale, or events per hundred patients? And how precisely was it estimated, which is what an interval or a standard deviation tells you. A paragraph that answers those four is a competent piece of graduate analysis even if it never names a test.
The vocabulary trap in this stage is the word significant. In a results section it means only that a result would be unlikely if there were truly no difference. It does not mean large, important, or worth changing practice for. Nurses use the word in its ordinary sense every day, and carrying that habit into a research paper is the most reliably penalized error in the course, because it is visible in a single sentence.
Written work at this stage is usually an analysis-focused paper on studies from your matrix, sometimes with a summary table, and occasionally a plan describing which analyses would answer your own question. Where a discussion accompanies it, expect a prompt about statistical versus clinical significance. Answer with a number from a real study rather than a definition, and remember posts do not reopen once submitted in Canvas.
The NR-559 Week 5 method, step by step
Six moves that turn a results table into paragraphs that hold up.
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Identify the outcome and the comparison before reading any number
Find the primary outcome and the two groups or two time points being set against each other. Results sections often report a dozen secondary comparisons, and students who start at the top of the table frequently write their whole paragraph about something the study was not designed to detect.
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Say the size of the difference in clinical units
Nineteen minutes shorter, four points lower on a scale that runs to sixty, eleven fewer events per hundred admissions. Translating the effect into units a bedside nurse would recognize is the sentence that makes a paper readable and it is usually the sentence graders look for first.
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Read the interval around the estimate before the p value
A confidence interval says how precisely the effect was pinned down. One running from trivial to substantial is telling you the study was too small to settle the question, and that message is completely hidden if you report the point estimate alone.
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Check whether the analysis matches the design and the data
Comparisons of two groups, comparisons of more than two, comparisons of the same people before and after, and relationships between variables all call for different families of test. You do not need to defend the choice mathematically. You need to notice when the description of the analysis does not match the description of the study.
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Account for what is missing from the results
Outcomes named in the methods that never reappear, participants who dropped out and are not in the analysis, subgroups reported only where they were favourable. Absence in a results section is information, and noticing it is a graduate-level move.
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Separate what was found from what the authors concluded
Write the finding in one sentence and the authors' interpretation in the next, then say whether the second is supported by the first. Discussion sections routinely stretch further than the numbers reach, and catching that gap is precisely what this stage rewards.
A layout and word budget for a results analysis
Our frame for writing up an analysis, sized for roughly 1,100 to 1,400 words. It is our own outline rather than anything the university issues, and your week's rubric outranks it wherever the two disagree.
| Section | What belongs in it | Word target |
|---|---|---|
| What was compared | The primary outcome, the groups or time points, and how the outcome was operationally defined. | 140 to 180 |
| The analytic approach | The tests or summaries used, described in plain language, with a note on whether they suit the data. | 170 to 210 |
| The finding in clinical units | Direction and magnitude expressed in real units with the counts and denominators that produced them. | 220 to 270 |
| Precision and uncertainty | Intervals or dispersion, what they imply about sample size, and how confident the estimate deserves to be. | 180 to 220 |
| What is absent | Missing outcomes, unanalyzed dropouts and selectively reported subgroups, with the effect of each. | 170 to 210 |
| Claim versus evidence | The authors' conclusion set beside the numbers, and your judgment on whether the distance is defensible. | 180 to 220 |
Evidence craft for reporting numbers
Every number arrives with its base and its window. Fourteen of 208 patients over one quarter is evidence. Seven percent is a figure the reader cannot weigh, cannot compare and cannot check. Denominators travel with counts in every sentence in this course.
Keep statistical vocabulary exact or leave it out. Significant means unlikely under the null hypothesis. A non-significant result is not evidence of no difference, especially in a small sample. Correlation describes co-movement and never causation. Misused vocabulary is far more damaging than plain description, because it is unmistakable to a grader who works in this field.
Distinguish statistical significance from clinical importance in an explicit sentence. A one-point change on a sixty-point scale can be statistically detectable in a large sample and clinically meaningless, and the reverse can happen in a small one. Write both judgments and label them, because rubrics in research courses often score them separately.
Never build a number of your own. Do not recompute percentages, average across studies by hand, or convert results into figures the authors did not report. Report what is on the page, and where the paper does not give you what you need, say that it does not.
Attribute interpretation to whoever made it. When the discussion section makes a claim, name the authors as its source rather than presenting it as fact. According to the authors is a small phrase that keeps the boundary between evidence and interpretation visible all the way through a paper.
Five mistakes that cost points in this week's territory
- Significant used to mean important. The single most penalized word in a graduate research course, and it costs a point every time it appears.
- P values reported as the finding. Without an effect size and a measure of precision, the reader cannot tell whether anything meaningful happened.
- A non-significant result read as proof of no effect. Small studies fail to detect real differences constantly, and absence of evidence is not evidence of absence.
- Percentages with no denominators. A rate change from 60 to 80 percent means nothing when nobody knows whether the base was 10 cases or 1,000.
- The authors' conclusion copied as the finding. Discussion sections overreach routinely, and repeating the overreach transfers it into your paper.
Before you submit
- The primary outcome is identified and defined operationally
- Every effect is stated in clinical units with direction and magnitude
- Counts appear with their denominators throughout
- A measure of precision accompanies each estimate
- Statistical significance and clinical importance are judged in separate sentences
- Missing outcomes and unanalyzed dropouts are named
- The authors' interpretation is attributed and then evaluated
Stuck in the results section for NR-559?
Send the rubric and the articles out of Canvas. A premium original draft comes back in 24 to 48 hours with effects reported in clinical units, precision stated, and the authors' claims measured against their own numbers, and revisions run until the grade lands.