AfroQuant
Make sense of your research data and statistical results
Practical quantitative research and statistical analysis support for researchers, academics and research teams.
Areas of support
Research design and measurement
- Research questions and hypotheses
- Variable identification and measurement
- Questionnaire and scale assessment
- Sample size and statistical power
- Measurement reliability and validity
Data preparation and exploration
- Data screening and cleaning
- Missing-data assessment
- Outlier identification
- Descriptive statistics
- Exploratory data analysis
- Statistical assumption checking
Statistical analysis
- Correlation and hypothesis testing
- t-tests and ANOVA
- Linear and logistic regression
- Regression diagnostics
- Mediation and moderation
- Exploratory factor analysis
Structural equation modelling
- Confirmatory factor analysis
- Measurement and structural models
- Model fit assessment
- Convergent and discriminant validity
- Direct and indirect effects
- Path analysis
- SEM interpretation and reporting
Tools
R
RStudio
lavaan
Python
IBM SPSS
IBM AMOS
Excel
Academic integrity
AfroQuant provides methodological guidance and analytical support, not academic ghostwriting. Researchers remain responsible for their own research decisions, interpretation, academic submissions and defence of findings.