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Assignment questions
NursingDiscussion postBiostatistics

DNP 830 Topic 4 DQ 2: clinical vs statistical significance

A p value above .05 does not mean nothing happened. This post is about defending a change that matters to patients when the arithmetic will not certify it — and about knowing when that defence is honest.

Editorial process

Last reviewed · August 15, 2026

01

Two kinds of significance, and only one is calculated

The prompt is built around a real and uncomfortable situation: your DPI project may not reach statistical significance, and you will still need to say something defensible about it. Start by being precise about what a p value is. It is the probability of observing a result at least as extreme as yours if there were truly no effect. It is not the probability that your intervention worked, and .07 is not a near miss on a threshold — it is a statement about how surprising your data would be under one assumption. Small practice-improvement projects frequently fail to reach .05 because they are underpowered, and an underpowered study that finds nothing has established very little either way. This is why the sample size calculation belongs in the same post: it tells you in advance how large an effect your project could have detected, and one powered only for an implausible effect was never going to reach significance.

Clinical significance asks a different question: is the size of the change large enough to matter to a patient or to a service. That question is answered with effect sizes, absolute differences and confidence intervals, not with p values, so report those. A fall in readmissions from eleven to seven on a unit is a real difference to seven households whatever the test says, and a confidence interval that runs from a substantial benefit to a small harm tells the reader far more than a single verdict of not significant. Where this argument goes wrong is when it becomes a way of rescuing any result at all. Be explicit that a clinically important change with a wide interval is a reason to keep looking rather than a finding, and say what a properly powered study would need. That is the difference between interpreting an underpowered result and explaining one away.

Likely learning objectives

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

  • 01
    State correctly what a p value does and does not report.
  • 02
    Distinguish clinical from statistical significance by the question each answers.
  • 03
    Use effect sizes and confidence intervals to support a clinical claim.
  • 04
    Recognise when a clinical-significance argument is being used to rescue a null result.
Assignment instructionsQuoted verbatim

Read the full question

Review every instruction before using the planning guidance that follows.

DNP 830 Topic 4 DQ 2 DQ 2 : On the chance that your DPI Project does not result in statistical significance, explain how you can justify clinical significance. While the goal of the DPI Project is to achieve clinical significance, you will also need to discuss if the data analysis also has statistical significance. Statistical significance (p = .05) helps determine whether a result is by chance. On the chance that your DPI Project does not result in statistical significance, explain how you can justify clinical significance. This topic helps you develop a basic understanding of statistics. Two distinct types of statistics are addressed: descriptive and inferential. In this assignment, you will have another opportunity to use the SPSS program. SPSS makes it easy to analyze data using specifc tests. This assignment will give you practice with t-tests, ANOVA, and communicating your results through a written summary. General Requirements: Use the following information to ensure successful completion of the assignment: Before beginning this assignment, be sure to view the tutorial videos located in the topic Resources. View the “Working With Inferential Statistics” tutorial, located in the DNP-830A folder of the DNP PI Workspace. Refer to the “Sample Analysis of Variance (ANOVA) Table” and “Sample Results of Several t Tests Table” in the topic Resources, as needed, to complete the table using APA style. Doctoral learners are required to use APA style for their writing assignments. The APA Style Guide is located in the Student Success Center. This assignment uses a rubric. Review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. You are not required to submit this assignment to LopesWrite. Learners will submit this assignment using the assignment dropbox in the digital classroom. In addition, learners must upload this deliverable to the Learner Dissertation Page (LDP) in the DNP PI Workspace for later use. Directions: Page 23 Grand Canyon University 2022 © Prepared on: Aug 24, 2022 Prior to beginning this assignment, complete the assigned readings and view the assigned videos. Using the data provided on the “HCUP State Inpatient Databases (SID) File Composition – Number of Discharges by Year” webpage, located in the topic Resources, conduct the appropriate statistical test in SPSS to address the following: 1. Describe the mean, standard deviation, and range of discharges in 2019. 2. Compare the number of discharges in 2019 in all states by region using an ANOVA. Are there signifcantly more discharges? Describe the assumption of variance between groups and within groups? Create a table of your results using APA style and attach as an appendix to your paper. Western States (Washington, Oregon, Idaho, Montana, Wyoming, California, Nevada, Utah, Arizona, New Mexico, Colorado Alaska, Hawaii); Mid-Western States (North Dakota, South Dakota, Nebraska, Kansas, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Indiana, Michigan, Ohio); Southern States (Maryland, Washington D.C, West Virginia, Virginia, Kentucky, North Carolina, South Carolina, Georgia, Florida, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Oklahoma, Texas); Northeastern States (Maine, Vermont, New Hampshire, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, Pennsylvania, Delaware). 3. Compare the number of discharges in all states between 2012 and 2019 using a paired t-test. Are there signifcantly more discharges in 2019 versus 2012? Describe the assumption of a paired samples t-test. Create a table for your results using APA style and attach as an appendix. 4. Write a 500–750-word summary of your results. 5. Attach your SPSS statistical outputs as an appendix to your paper. Portfolio Practice Immersion Hours: It may be possible to earn portfolio practice immersion hours for this assignment. Enter the following after the References section of your paper: Practice Immersion Hours Completion Statement DNP-830A I, (INSERT NAME), verify that I have completed and logged (NUMBER OF) clock minutes/hours in association with the goals and objectives for this assignment. I also have tracked said practice immersion hours in the Lopes Activity Tracker for verifcation purposes and will be sure that all approvals are in place from my faculty and practice immersion preceptor/mentor before the end of the course. Lopes Activity Tracker Submission For this assignment, you will need to submit a summary of practice immersion hours earned up to this point in the course. All practice immersion hours showing on this summary must be approved by your preceptor/ mentor. It is your responsibility to ensure your preceptor/mentor approves all submissions within 72 hours. Download a summary of your practice immersion hours from Lopes Activity Tracker. Save the fle and submit it through the assignment dropbox in the digital classroom. In addition, learners must upload this deliverable to the Learner Dissertation Page (LDP) in the DNP PI Workspace for later use. This submission is required in order to receive a fnal grade in the course. In order to receive a passing grade in the course, learners are required to have met the required number of approved practice immersion hours.
02

Turn the brief into deliverables

  1. 01
    A sample size calculation with its inputs stated.
  2. 02
    An accurate account of what your p value would mean.
  3. 03
    An effect size or absolute difference with a confidence interval.
  4. 04
    An honest boundary on what an underpowered result can support.
03

Compute the size, then argue the meaning

01

The sample size calculation

Compute the required sample and state every input assumption.

02

What a p value reports

Define statistical significance accurately.

03

Clinical significance and how it is evidenced

Show what effect sizes and intervals contribute that p values cannot.

04

Where the argument stops

State the limits of interpreting an underpowered null result.

04

Sources on effect size and clinical importance

Recommended databases

  • StatPearls statistics chapters
  • PubMed Central
  • Your SPSS or G*Power materials
  • CINAHL

Search sequence

  1. 1.
    Find the minimal clinically important difference for your outcome if one has been published.
  2. 2.
    Look up how power, effect size and sample size trade against each other before calculating.
  3. 3.
    Read one paper that reports a non-significant result honestly and note how it is framed.
  4. 4.
    Check the correct interpretation of a confidence interval that crosses no effect.
05

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.

  1. 01

    Statistical Significance

    StatPearls, NCBI Bookshelf · 2023

    Defines statistical significance precisely, which is what stops the p value being described as the probability the intervention worked.

  2. 02

    Hypothesis Testing, P Values, Confidence Intervals, and Significance

    StatPearls, NCBI Bookshelf · 2023

    Covers p values and confidence intervals together, which is the pairing the clinical-significance argument depends on.

  3. 03

    Type I and Type II Errors and Statistical Power

    StatPearls, NCBI Bookshelf · 2023

    Explains power and Type II error, which is why a small project's null result establishes so little.

  4. 04

    Practical guide to calculate sample size for chi-square test in biomedical research

    Journal of Family Medicine and Primary Care · 2025

    A worked sample size calculation showing which inputs must be declared for the result to be checkable.

06

Review before submission

Common mistakes

  • Describing a p value as the probability the intervention worked.
  • Treating clinical significance as a way of salvaging any non-significant result.
  • Reporting a p value with no effect size beside it.
  • Running the sample size calculation without stating the effect size it assumed.

Submission checklist

  • Is your definition of the p value technically correct?
  • Did you report an effect size and interval, not just significance?
  • Are the inputs to your sample size calculation stated?
  • Have you said where the clinical-significance argument stops being honest?

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Written by

Aaron Bishop

MA, Education

assignment interpretation and research-methods coaching across disciplines

Aaron leads the EssayCrackers editorial desk. He works on how assignment briefs are read — what a rubric is actually asking for, and where students most often answer a different question than the one set.

Reviewed by

Dr. Nathan Cole

PhD, Rhetoric & Composition

Argumentation and thesis development

Nathan teaches first-year composition and directs a university writing center. He reviews EssayCrackers guides for argumentative soundness and citation accuracy.

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