Analysis plan
Map every question or hypothesis to variables, coding, assumptions, tests, decision rules, and reporting outputs.
Quantitative analysis
Choose analysis that answers the question—not analysis for display.
We support defensible quantitative workflows from variable coding and data screening through statistical output, interpretation, reporting, and alignment with hypotheses.
Why it matters
Software output is not the same as statistical reasoning.
The correct technique depends on the research design, measurement level, sampling process, assumptions, model structure, and question being answered. We begin with those decisions before running tests.
Support is available for SPSS, AMOS, and SmartPLS workflows, including data preparation, descriptive analysis, reliability, group comparisons, regression, mediation, moderation, measurement models, and structural models where appropriate.
What support covers
Focused help for the decisions that affect quality.
Every engagement is scoped to the material supplied and the work actually required.
Data quality
Review missing values, coding errors, outliers, distributions, scale scoring, and analysis-ready structure.
Interpretation
Explain effect sizes, uncertainty, model fit, limitations, and what the results do—and do not—support.
Working process
A clear sequence from review to final check.
The exact milestones vary by project, but the work remains traceable and decision-led.
- 01
Review the proposal, instrument, codebook, dataset, and intended model.
- 02
Freeze an analysis plan before interpreting outputs.
- 03
Run and document the agreed checks and statistical procedures.
- 04
Present traceable tables, figures, interpretations, and a limitation-aware results narrative.
What to prepare
Send enough context for an accurate scope.
- Original dataset and codebook
- Questionnaire or measurement sources
- Research questions, hypotheses, and conceptual model
- Any prior cleaning steps or software output
Responsible support
- You remain the author and decision-maker for your research.
- We do not guarantee supervisor approval, a degree outcome, or journal acceptance.
- We do not fabricate participants, data, citations, approvals, or research findings.
- The agreed scope, source files, deadline, and revision terms are confirmed before work begins.
Questions
Before you begin.
For project-specific questions, share the programme, topic, current stage, deadline, and exact support needed.
Which software do you support?
The institute commonly supports SPSS, AMOS, and SmartPLS. The suitable tool depends on the model and method, not preference alone.
Can you make insignificant results significant?
No. Results must reflect the data and valid method. We can diagnose design, coding, assumption, power, or model-specification issues without manipulating findings.
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