What Actually Happens When Your Regression Fails The Hypothesis

How do I ethically report a non‑significant regression when my prospectus hypothesis is contradicted?

When the SPSS output shows a p‑value above .05, the most honest move is to present that result exactly as it appears and then explain why it matters for your theory. Your committee is looking for transparency, not a perfect match between expectation and outcome. Start the results paragraph with the statistic itself – for example, “The regression coefficient for X on Y was .12 (SE = .08), t(96) = 1.50, p = .14.” Follow that with a brief interpretation that acknowledges the non‑significance and ties it back to the theoretical framework you outlined in Chapter 1. You can argue that the finding suggests the relationship is weaker than predicted, or that the current sample may lack power, and propose how the full study will address these limits. By framing the result as a legitimate piece of evidence rather than a failure, you demonstrate scholarly maturity and keep the prospectus on track without a wholesale rewrite.

What terminology does my committee expect when I discuss a contradictory finding?

Committee members scan the prospectus for specific language that signals you understand the research design and its statistical conventions. In the methods and results sections, they look for the exact terms “null hypothesis,” “alternative hypothesis,” “statistical significance,” “effect size,” and “confidence interval.” When you describe the regression, use “beta coefficient,” “standard error,” and “t‑statistic” rather than vague phrases like “big effect.” In the discussion, the phrase “fails to reject the null hypothesis” is preferred over “the hypothesis was disproved.” If you refer back to your theoretical model, use “theory‑driven expectation” or “conceptual linkage” to show continuity.

Here are three key labels that should appear in your prospectus:

• Hypothesis statement: clearly labeled as H1, H2, etc., and linked to a specific variable.
• Statistical outcome: report the exact p‑value, t‑value, degrees of freedom, and confidence interval.
• Theoretical implication: a sentence that explicitly connects the statistical result to the framework introduced in Chapter 1.

Missing any of these cues often triggers a request for revision because the committee cannot see whether you have a coherent argument or simply omitted the problematic result.

Which technical pitfalls could be causing the non‑significant p‑value?

Before you accept the result at face value, double‑check the regression assumptions that SPSS automatically tests. First, verify linearity by inspecting a scatterplot of residuals; a curved pattern may indicate a missed transformation. Second, look at multicollinearity diagnostics – VIF values above 5 suggest that predictors are overlapping, which can inflate standard errors and push p‑values above .05. Third, assess homoscedasticity; a Breusch‑Pagan test (or the SPSS “Heteroskedasticity” option) will tell you if the variance of residuals changes across levels of the predictor.

If any of these diagnostics flag a problem, you can often correct it without re‑collecting data. For instance, centering variables can reduce multicollinearity, and applying a log transformation can restore linearity. Also, consider statistical power: with a sample of 50, a medium effect size may not reach significance. A quick power calculator (even a spreadsheet) can show whether your current N is sufficient. If power is low, you can acknowledge this limitation in the prospectus and propose a larger sample for the full dissertation.

Finally, make sure the SPSS table follows APA 7 format: include the unstandardized B, the standardized β, SE, t, and p in separate columns, and label the table “Table 1. Regression predicting Y from X.” A mis‑formatted table can be mistaken for a sloppy analysis, prompting a request for revision.

How can I keep my prospectus ethically sound and avoid integrity flags?

Ethical reporting means you do not spin the non‑significant result into a “trend” or fabricate additional analyses to force significance. Committees use plagiarism detectors and AI‑checkers to spot overly generic language; a paragraph that simply repeats textbook definitions without citation can raise a red flag. Write the interpretation in your own voice, referencing the specific theory you built earlier, and cite the original source of that theory in the discussion.

Two critical warnings:

• Do NOT fabricate data or selectively report only the significant predictors.
• p < .05 is the conventional cutoff, but reporting the exact p‑value (e.g., p = .14) is required.

If you need to include additional analyses (e.g., a robustness check), label them as exploratory and keep them separate from the primary hypothesis test. This transparency shows the committee that you understand the limits of your current evidence and are planning a more rigorous follow‑up.

What quick plan can I follow in the next 48 hours?

Time is tight, but a focused sprint can get your prospectus ready for submission. Follow this checklist, allocating roughly the time shown next to each item:

1. Re‑run the regression with diagnostics (15 min). Check VIF, residual plots, and homoscedasticity.
2. Adjust any obvious issues – center variables or apply a log transform if needed (10 min).
3. Update the results table to APA 7 style, inserting the exact statistics (10 min).
4. Write a concise results paragraph that starts with the statistic, then adds a brief interpretation linking back to your theory (20 min).
5. Draft a discussion paragraph that acknowledges the non‑significance, cites power considerations, and outlines how the full study will address them (30 min).
6. Insert the three terminology cues (hypothesis label, statistical outcome, theoretical implication) into the appropriate sections (5 min).
7. Proofread for plagiarism‑safe language: replace any copied textbook sentences with your own phrasing (10 min).
8. Final format check: ensure headings, table numbers, and reference style match the department guide (5 min).

When you finish, you’ll have a prospectus that is honest, technically sound, and formatted exactly as your committee expects – all without a massive rewrite.

Decision matrix for reporting contradictory SPSS results