NursingDiscussion postInferential statistics

t Tests and ANOVA in Clinical Practice: DQ planning guide

Find a nursing research article that used a t test or ANOVA and judge what the statistic did for it. The prompt's fourth question offers 'weakened' as an answer, and taking that option seriously is what separates an appraisal from a summary.

Aug 5, 2026Updated Aug 10, 2026

Editorial process

Last reviewed · August 5, 2026

Written by

Aaron Bishop

MA, Education

assignment interpretation and research-methods coaching across disciplines

Reviewed by

Dr. Nathan Cole

PhD, Rhetoric & Composition

Argumentation and thesis development

On this page

Interpret the task
Assignment instructions
Deliverables
Proposed outline
Research plan
Reference shortlist
Final review

Appraising a statistic, not explaining one

You are not being asked to run a t test or an ANOVA, and you are not being asked to explain what they are. You are being asked to appraise somebody else's use of one. That distinction decides the post. A response that opens with a paragraph defining inferential statistics has spent its opening on material the prompt already supplied in its own preamble, and the four numbered headings — topic, summary, purpose and value, strengthened-or-weakened — leave no room for a tutorial. The article you pick is the object of study; the statistic is the lens you examine it through. A useful test of your draft: delete every sentence that would still be true if you had chosen a different article. Whatever survives is the appraisal, and the prompt is marking that. Everything else is preamble the marker has already read.

Choosing the article is therefore the most consequential decision, and it is made before you write a word. It has to be a primary research report — not a review, not a quality-improvement write-up — and it has to state its inferential test explicitly. The prompt gives you the selection rule in its own preamble: two groups means a t test, three or more means ANOVA. A paper comparing an intervention arm with a control arm should be reporting a t test; a paper comparing three dosing schedules or four units should be reporting ANOVA. If you cannot find the test named in the methods or under a table, pick a different paper rather than inferring which one was used. One more filter is worth applying early: the brief limits you to three references from the list in the instructions area, so an article you cannot reach through those resources costs you the citation you need.

Question 4 is where the marks separate, because it offers weakened as a live answer and most posts never take it seriously. A study can run its test perfectly and still apply weakly to practice:

What you find in the article	Why it weakens the application	What to write instead of “the results were significant”
A p value and nothing else	Statistical significance says the difference is unlikely to be chance; it says nothing about how big the difference is	Name the missing effect size — Cohen's d for a t test, eta-squared for an ANOVA — and say what its absence prevents you concluding
A very large sample	With enough participants a clinically trivial difference becomes statistically significant	Report the actual magnitude alongside the p value and judge whether it would change a nursing decision
A significant ANOVA with no post-hoc test	The omnibus F says a difference exists somewhere among the groups; it does not say which groups differ	State that the pairwise comparison is missing, so the paper cannot support a claim about any specific pair
Assumptions not addressed	ANOVA assumes independent random samples, normality and roughly equal variances	Say which assumption is unexamined and whether the design makes it plausible anyway

The evaluation in question 3 is about the study's value to your chosen topic, not about the statistics again. This is where a reporting checklist earns its keep: most nursing articles that use a t test or ANOVA are observational, and STROBE names what an observational report ought to contain — how participants were selected, how variables were measured, how missing data were handled. Judging the paper against a published standard is a stronger move than asserting it was well conducted, and it gives you something concrete to say about sample and data sources in question 2. It also gives question 3 a shape it otherwise lacks — 'purpose and value' is an invitation to waffle until you attach it to something checkable, and a reporting checklist is the cheapest thing to attach it to. Say which items the paper satisfies and which it passes over.

Two mechanical requirements are easy to lose. The brief prescribes level-one headings numbered as in the instructions, so the four questions become four headings rather than four paragraphs of continuous prose — structure is being marked, not just content. And it asks for a minimum of 550 words with at least three references, with a complete APA citation of your chosen article included in the summary. Cite the article you appraised in full; a post that discusses a study without a retrievable citation cannot be checked by the reader it is written for. Word count is a floor rather than a target here, and 550 words across four headings is roughly 140 each, which is about one substantial paragraph per question — worth knowing before you spend three hundred of them on the summary.

Likely learning objectives

Inferred from the brief — check these against your own rubric.

01
Select a primary research article whose inferential test is explicitly reported.
02
Explain why the number of groups compared determines whether a t test or an ANOVA is appropriate.
03
Distinguish statistical significance from clinical importance using effect size.
04
Appraise an observational study against a published reporting standard rather than by impression.
05
Judge whether an inferential statistic strengthened or weakened a study's application to practice, and defend either verdict.

Assignment instructionsQuoted verbatim

Read the full question

Review every instruction before using the planning guidance that follows.

Inferential statistics enable researchers to apply the data they gather and the conclusions they draw from a particular sample to a larger population. As the name implies, inferential statistics focus on inferring whether there is a relationship between two or more variables. These statistical analyses include t tests and analysis of variance (ANOVA). t Tests are part of a group of statistical tests that test hypotheses; in fact, it is necessary to formulate a hypothesis in order to use a t test, because the results of the test can only be interpreted in the context of a scientific hypothesis. Inferential statistics such as t tests work well for comparing two groups. Although mathematically equivalent to the t test, ANOVA allows for the comparison of more than two groups. Therefore, when three or more groups are involved, the ANOVA should be used. In this week’s Discussion, you are asked to locate a current research article that utilizes either a t test or ANOVA analysis. You provide a summary of the research study and of the study’s application to evidence-based practice. You also examine the article’s use of a t test or ANOVA and how either of those statistical analysis tools helped to inform the article’s conclusions and recommendations. To prepare: Tests and ANOVA in Clinical Practice DQ Consider some of the important issues in health care delivery or nursing practice today. Bring to mind the topics to which you have been exposed through previous courses in your program of study, as well as any news items that have caught your attention recently. Select one topic to consider for this Discussion. Next, review journal, newspaper, and Internet articles that provide credible information on your topic (you can choose any nursing topic from Confidentiality or Work Place Bullying or any other nursing related issue that will be easy to locate a scholarly research article on which uses a t test or ANOVA) Then, select one research article on which to focus that used inferential statistical analysis (either a t test or ANOVA) to study the topic. With information from the Learning Resources in mind, evaluate the purpose and value of the research study discussed in your selected article and consider the following questions: Who comprised the sample in this study? What were the sources of data? What inferential statistic was used to analyze the data collected (t test or ANOVA)? What were the findings? Ask yourself: How did using an inferential statistic bring value to the research study? Did it increase the study’s application to evidence-based practice? By tomorrow Wednesday 09/27/17, 8 pm, write a minimum of 550 words essay in APA format with a minimum of 3 references from the list in the instructions area. Include the level one headings as numbered below: Post a cohesive response that addresses the following: Tests and ANOVA in Clinical Practice DQ 1) Identify the topic you selected in the first line of your posting. (you can choose any nursing topic from Confidentiality or Work Place Bullying or any other nursing related issue that will be easy to locate a scholarly research article on which uses a t test or ANOVA) 2) Summarize the study discussed in your selected research article and provide a complete APA citation. Include in your summary the sample, data sources, inferential statistic utilized, and findings. 3) Evaluate the purpose and value of this particular research study to the topic. 4) Did using inferential statistics strengthen or weaken the study’s application to evidence-based practice? Tests and ANOVA in Clinical Practice DQ Required Readings Gray, J.R., Grove, S.K., & Sutherland, S. (2017). Burns, and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (8th ed.). St. Louis, MO: Saunders Elsevier. Chapter 25, “Using Statistics to Determine Differences” This excerpt elaborates on how statistics are used to examine causality using procedures such as contingency tables, chi-squares, t tests, and analysis of variance (ANOVA). Statistics and Data Analysis for Nursing Research Chapter 5, “Statistical Inference” This chapter discusses inferential statistics, sampling error, sampling distributions, and the laws of probability. The chapter also introduces key terms such as standard error of mean, hypothesis testing, and parametric test. Chapter 6, “t Tests: Testing Two Mean Differences” This chapter considers the various forms of the t test, including the two-sample t test, Kolmogrov-Smirnov test, independent groups t test, and dependent groups t test. The chapter also discusses the many variables involved in these tests such as effect size, meta-analysis, and Cohen’s d. Chapter 7, “Analysis of Variance” (pp. 137–146 and 155–158) The first part of this chapter introduces the basic assumptions, requirements, general logic, and terminology surrounding analysis of variance (ANOVA). The second excerpt focuses on sampling distribution of the F ratio and the null and alternative hypotheses. Jadcherla, S. R., Wang, M., Vijayapal, A. S., & Leuthner, S. R. (2010). Impact of prematurity and co-morbidities on feeding milestones in neonates: A retrospective study. Journal of Perinatology, 30(3), 201–208. doi:10.1038/jp.2009.149 This article outlines the procedures and results of a retrospective study of how perinatal and comorbidity factors affect the rate at which infants meet feeding milestones. The article also includes an application of inferential statistics to the results of the study. Optional Resources Shin, J. H. (2009). Application of repeated-measures analysis of variance and hierarchical linear model in nursing research. Nursing Research, 58(3), 211–217. doi:10.1097/NNR.0b013e318199b5ae Walden University. (n.d.). Analysis of variance. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_analysis_of_variance_anova.html Walden University. (n.d.). Inferential statistics. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_inferential_stats_and_hypothesis_testing.html Walden University. (n.d.). t-Tests. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_ttests.html

The 550 words, three references and four headings

01
Minimum 550 words, APA format.
02
Minimum 3 references, from the list in the instructions area.
03
Four numbered level-one headings matching the four prompt questions.
04
The topic identified in the first line of the posting.
05
A complete APA citation of the selected research article, inside the summary.
06
Sample, data sources, inferential statistic and findings, all named in the summary.

Working through the four numbered questions

1) Identify the topic, in the first line

Name the practice issue you selected before any other sentence, as the brief instructs.

2) Summarise the study, with the citation inside it

Give sample, data sources, the inferential statistic used, and the findings, with a complete APA citation of the article.

Say why this test, for this design

Connect the number of groups compared to the test reported — two groups to a t test, three or more to ANOVA — and note whether the paper's choice fits.

3) Evaluate purpose and value against a standard

Judge the study's contribution to your topic, using an explicit yardstick such as STROBE's expectations for reporting participants, variables and missing data.

4) Strengthened or weakened — commit to one

Answer the question directly, citing effect size, sample size, post-hoc testing or unexamined assumptions as the reason.

Close on what a nurse could do with it

One or two sentences on whether the finding is actionable in practice, given what the statistic did and did not establish.

How do you find an article that names its test?

Recommended databases

CINAHL
PubMed / PMC
Journal of Graduate Medical Education
EQUATOR Network

Search sequence

1.
Search CINAHL or PubMed for your topic combined with 'analysis of variance' or 't-test' and filter to primary research; the test must appear in the abstract or methods, not be inferred.
2.
Confirm the number of groups compared before accepting the article — this is the fastest check that the reported test was the right one.
3.
Look up effect size reporting so question 4 can be answered with a criterion rather than an impression.
4.
Check the article against STROBE if it is observational, and note any reporting element that is missing.
5.
Confirm which three references your instructions area permits; the brief restricts you to that list.

Reference shortlist

These are authoritative starting points, not a ready-made bibliography. A qualified reviewer must confirm that each source fits the assignment and supports the claim beside which it is cited.

Nothing here is cleared for citation until you have read it.

01
Using Effect Size—or Why the P Value Is Not Enough
Journal of Graduate Medical Education (via PubMed Central) · 2012
The argument question 4 needs: significance and magnitude are different claims, and with a large sample a trivial difference becomes significant. Its aspirin example (p < .00001 with r-squared of .001) is a ready-made illustration.
02
13.1 One-Way ANOVA
OpenStax, Introductory Statistics 2e · 2023
The five assumptions behind ANOVA — normality, independent random sampling, equal variances, a categorical independent variable, a numerical dependent variable — which give you a checklist for judging whether the paper's test was appropriate.
03
10.1 Two Population Means with Unknown Standard Deviations
OpenStax, Introductory Statistics 2e · 2023
The conditions for the two-sample t test, including why variances should not be pooled when the population standard deviations may differ — the counterpart check if your article compares two groups.
04
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies
EQUATOR Network · 2007
A published yardstick for question 3. Most nursing articles using these tests are observational, and STROBE names what should have been reported about participants, variables and missing data.
05
Impact of prematurity and co-morbidities on feeding milestones in neonates: a retrospective study
Journal of Perinatology (via PubMed) · 2010
The worked example named in this course's own required readings: a retrospective study of 186 infants that applies inferential statistics to comorbidity effects, useful as a model of what a suitable article looks like.

Before you post: did you consider 'weakened'?

Common mistakes

Writing a tutorial on inferential statistics. The prompt's own preamble already defines t tests and ANOVA; repeating it consumes the word budget and answers nothing.
Answering question 4 with 'strengthened' by default. 'Weakened' is offered, and a study with no effect size, or a significant ANOVA with no post-hoc comparison, genuinely applies weakly to practice.
Choosing an article that does not name its test. Inferring that a t test was 'probably' used makes every subsequent claim unverifiable.
Treating a small p value as evidence of a large effect. With a big enough sample a clinically meaningless difference reaches significance.
Reading a significant omnibus F as evidence that specific groups differ. Without a post-hoc test the paper has not identified any pair.
Running the four questions together as continuous prose when numbered level-one headings are prescribed.
Summarising the article's conclusions instead of its methods. Questions 2 and 3 ask for sample, data sources and statistic — the parts most summaries skip.

Submission checklist

Topic stated in the first line, before anything else.
Article is primary research and names its inferential test in the methods or a table.
The test matches the number of groups compared.
Complete APA citation of the article appears inside the summary.
Sample, data sources, statistic and findings each explicitly identified.
Question 4 answered with a verdict and a reason, not a restatement of the findings.
Effect size addressed — present and interpreted, or named as absent.
Four numbered level-one headings present.
At least 550 words and at least three references.

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