Data Cleaning, Assumptions & Descriptive Analysis

Ensure your data is clean, defensible, and analysis-ready.
This service provides professional data screening, assumption checks, and descriptive statistics for one dataset, with a clear written interpretation explaining whether your data is suitable for further statistical or psychometric analysis.

This service provides a professional data screening and diagnostic analysis to ensure your dataset is suitable for statistical modelling and interpretation. It is ideal as a first-stage analysis before regression, factor analysis, SEM, or other advanced methods.

The focus is on data quality, assumptions, and clarity, giving you a clean, defensible foundation for further analysis or reporting.

What’s Included 

This service covers one dataset and includes:

• Import and preparation of one dataset
• Missing data analysis, including:
  • Extent and patterns of missingness
  • Clear recommendation for handling (e.g. listwise deletion vs. imputation strategy)
• Outlier checks:
  • Univariate outliers
  • Multivariate outliers (where appropriate)
• Normality and assumption diagnostics relevant to planned analyses
• Descriptive statistics (means, SDs, ranges)
• Correlation matrix (where appropriate)
• Short explanation (approximately 1–2 pages), explaining:
  • Data quality
  • Assumption suitability
  • Key issues to address before modelling

All outputs are presented clearly and professionally.

Deliverables

You will receive:

• A concise written report (Word or PDF)
• Tables ready for inclusion in reports or theses
• Clear guidance on whether your data is suitable for further analysis

What This Service Does Not Include: 

To keep scope clear and pricing fair, this service does not include:

• Exploratory or Confirmatory Factor Analysis (EFA / CFA)
• Structural Equation Modelling (SEM)
• Rasch Analysis
• Regression, mediation, or moderation analysis
• Scale validation or item reduction

These are available as separate services.

Who This Service Is For

• Researchers preparing data for further statistical analysis
• Organisations checking data quality before modelling or reporting
• Students or professionals needing a defensible data screening stage
• Anyone unsure whether their dataset meets analytical assumptions

How It Works

1. Purchase the service
2. Upload your dataset and brief description of intended analyses
3. Data screening and diagnostics are completed
4. You receive your report and tables

Frequently Asked Questions

What type of data can you work with?

Survey data, assessment data, organisational datasets, and research datasets in common formats (e.g. SPSS, Excel, CSV). If you’re unsure, you can ask before purchasing.

Is there a limit on sample size?

This service is priced for typical small-to-medium datasets. Very large or complex datasets may require a custom quote, which will be flagged before work begins.

Does this include data imputation?

This service includes a recommendation on whether imputation is appropriate and which approach is suitable. Actual imputation and re-analysis are available as an add-on or within higher-tier services.

Will I receive explanation, or just tables?

You will receive both:

• Professional tables

• A 1–2 page written explanation explaining data quality, assumptions, and next steps in plain language

Can this be used before advanced analysis?

Yes. This service is designed specifically as a pre-analysis step before regression, factor analysis, SEM, Rasch, or other advanced methods.

Is this suitable for organisational or professional use?

Yes. Outputs are written to a professional standard and are suitable for internal reports, audits, and research documentation.