A p-value greater than 0.05 means your result is not statistically significant. In simple terms, your data does not provide enough evidence to support your hypothesis.
If you just ran your analysis and saw this, you’re likely asking:
- Did I do something wrong?
- Will this affect my dissertation?
- Do I need to redo everything?
You are not alone. This is one of the most common points where students get stuck after running analysis in SPSS.
Why your p-value is greater than 0.05 in SPSS
At this stage, the issue is rarely SPSS itself. The problem usually comes from how the data was collected, structured, or analyzed.
1. Your sample size is too small
Small samples reduce your ability to detect real effects. Even if a relationship exists, your results may still appear non-significant. If you are unsure whether your sample size was adequate, revisit how it should be calculated using the Cochran formula calculator for sample size.
2. Weak or no relationship between variables
Sometimes, there is simply no meaningful relationship in your data. If you are testing relationships, make sure you correctly ran and interpreted correlation using this guide on bivariate correlation in SPSS.
3. Poor questionnaire design
This is one of the most overlooked problems.
If your questions:
- do not measure the right variables
- are unclear or inconsistent
- use poorly structured scales
then your results will be weak.
If your study is survey-based, revisit your structure through survey design to identify possible issues.
4. You used the wrong statistical test
Using the wrong test leads to misleading results.
For example:
- Using Pearson correlation on ordinal data
- Running regression without checking assumptions
If you are unsure whether your test was appropriate, review how analysis should be done using SPSS data analysis.
5. Issues with how your data was coded
Incorrect coding can distort your results. This is common with Likert scale data. If that applies to your study, check this guide on how to analyze Likert scale data in SPSS.
Is a p-value greater than 0.05 bad?
No.
A p-value greater than 0.05 does not mean your research failed.
It simply means:
- your hypothesis is not supported by the data
- the relationship or effect is not statistically strong
Many dissertations include non-significant results. What matters is how you interpret and present them.
What to do if your p-value is greater than 0.05
This is where most students get stuck. Follow this structured approach.
Step 1: Check your assumptions
Before interpreting results, confirm:
- normality
- homogeneity
- linearity
If assumptions are violated, your p-value may not be reliable.
You can review assumption testing using normality test in SPSS.
Step 2: Confirm your test selection
Make sure your test matches:
- your data type
- your research question
If not, switch to a more appropriate method.
For example, if you used the wrong test, compare approaches like ANOVA vs t-test.
Step 3: Re-check your data structure
Look at:
- missing values
- outliers
- incorrect coding
Even small errors can affect significance.
Step 4: Focus on correct interpretation
Do not try to “fix” your p-value artificially.
Instead:
- explain why results are not significant
- link findings to theory
- discuss limitations clearly
Step 5: Strengthen your write-up
This is where most marks are gained or lost.
If you are unsure how to present results properly, follow this guide on how to write up a dissertation analysis using SPSS.
How to report a p-value greater than 0.05 (APA example)
Example:
The results showed no statistically significant relationship between X and Y (p > 0.05), indicating that the independent variable did not significantly influence the dependent variable.
Keep your interpretation:
- clear
- direct
- aligned with your research objectives
Common mistakes students make
- Assuming non-significant results mean failure
- Using the wrong statistical test
- Ignoring data quality issues
- Misinterpreting SPSS output
- Failing to explain results properly
These are the exact reasons many students struggle with Chapter 4.
When you should be concerned
You need to take action if:
- your supervisor questions your analysis
- your results contradict your research design
- you cannot explain your findings
- your SPSS output looks inconsistent
At this point, the issue is no longer simple interpretation.
It becomes a data analysis problem that needs correction.
If you are stuck here, structured support from dissertation data analysis services can help you resolve errors and complete your analysis correctly.
Conclusion
A p-value greater than 0.05 does not mean your work is wrong.
It means your data does not show strong evidence of an effect.
What determines your grade is not the p-value itself, but:
- how accurately you interpret it
- how clearly you explain it
- how well your analysis aligns with your research design
Most students struggle at this exact point because they focus on “getting significant results” instead of presenting correct analysis.
If you understand and explain your results properly, your work remains valid and defensible.
FAQ
What does p-value greater than 0.05 mean in SPSS?
It means your result is not statistically significant. Your data does not provide strong evidence to support your hypothesis.
Is p > 0.05 a bad result in a dissertation?
No. Many dissertations report non-significant results. What matters is how you interpret and justify them.
Can I still pass if my results are not significant?
Yes. You can still pass if your analysis is correct and your interpretation is clear and academically sound.
Why is my p-value greater than 0.05?
Common reasons include small sample size, weak relationships between variables, poor data quality, or using the wrong statistical test.
Should I redo my analysis if p > 0.05?
Not always. First check your assumptions, data quality, and test selection. Only redo analysis if there is a methodological error.
How do I explain non-significant results in Chapter 4?
State that the results were not statistically significant, interpret what that means, and link it to theory or possible limitations.
Can I change my data to get a lower p-value?
No. Manipulating data is academically unacceptable. You should report results honestly and interpret them correctly.
What should I do if my supervisor rejects my SPSS results?
You need to review your methodology, test selection, and interpretation. In many cases, the issue is not the result but how it was presented.
Does p > 0.05 mean there is no relationship at all?
Not necessarily. It means there is no strong statistical evidence of a relationship in your sample.
Where can I get help with SPSS interpretation?
If you are stuck interpreting results or completing your analysis, you can get structured support from SPSS dissertation help or help with SPSS analysis.
