Prepare
Review structure, completeness, coding and data quality before analysis begins.
Data Analysis & Interpretation
Turn Research Data Into Meaningful Findings
Collecting data is only part of the research process. The value of your data depends on whether it is analysed appropriately and interpreted in relation to your research questions.
Analysis with purpose
The Method Must Serve the Research Question
A technically complex analysis is not automatically the right analysis. The approach must fit the study, the data and the claims the research is designed to examine.
Select
Choose methods that fit the design, variables, assumptions and questions.
Interpret
Explain what the patterns mean within the limits of the study.
Communicate
Present findings clearly through narrative, tables, charts and evidence.
Two analytical pathways
Different Data Requires Different Reasoning
Quantitative and qualitative work answer questions in different ways. Each pathway requires careful preparation, transparent decisions and disciplined interpretation.
Pathway 01
Quantitative
- Data cleaning and preparation
- Descriptive statistics
- Inferential statistics
- Correlation analysis
- Regression analysis
- Hypothesis testing
- Survey-data analysis
- SPSS
- Excel
- R where appropriate
- Tables and charts
- Statistical interpretation
Pathway 02
Qualitative
- Data organisation
- Coding
- Theme development
- Thematic analysis
- Theme/subtheme refinement
- Interpretation
- Evidence presentation
- Connection to research questions
From data to discussion
A Clear Analytical Workflow
The work moves from preparation to a defensible interpretation that connects directly with the study's questions.
- 01
Prepare
- 02
Analyse
- 03
Interpret
- 04
Present
- 05
Connect to Research Questions
Sound analysis respects what the data can—and cannot—support.
Analytical quality
Methods Must Align With the Study
Analytical decisions should be justified by the structure and purpose of the research, not selected simply because a method is familiar or produces a preferred result.
- Data type
- Research design
- Research questions
- Analytical assumptions
- Sample and study context
No responsible analysis can promise statistical significance or a predetermined conclusion. Findings are interpreted according to the evidence, assumptions and limits of the study.
Connected support
Related Services
Research needs often overlap. These services may support an adjoining stage of the same project.
Common questions
Frequently Asked Questions
Clear answers to common questions about this service and how support is approached.
Can you analyse an existing dataset?
Yes. We first review the dataset, variables, research questions, collection process and any existing analysis before agreeing the appropriate scope.
Which software do you use?
Software depends on the study and data. Support may involve SPSS, Excel or R where appropriate, alongside qualitative coding and thematic-analysis methods.
Can you help interpret SPSS output?
Yes. Output can be reviewed and explained in relation to the test assumptions, research questions, study design and limits of the data.
Do you support qualitative thematic analysis?
Yes. Support can include data organisation, coding, theme development, refinement and evidence-based interpretation linked to the research questions.
Can you help present findings in tables and charts?
Yes. Tables and charts can be selected and refined to communicate findings accurately, clearly and without overstating what the data supports.
Make Better Sense of Your Research Data
Tell us about your dataset, research questions and current analytical challenge. We can help determine an appropriate, defensible path from data to findings.
Request Research Support