Publication-quality statistical analysis for research papers, theses, and dissertations — SPSS, R, Python, AMOS, Stata. Descriptive, inferential, multivariate, SEM, survival analysis, and more — with complete written interpretation ready for publication.
Our biostatisticians and research methodologists cover the full range of statistical analysis techniques used in academic research — from basic frequency tables to complex structural equation models. Every analysis is delivered with clear written interpretation ready to copy into your paper.
Means, medians, standard deviations, frequency distributions, normality testing (Shapiro-Wilk, Kolmogorov-Smirnov), histograms, box plots, and demographic characteristic tables — all properly formatted for journal submission.
Independent and paired t-tests, one-way and two-way ANOVA, ANCOVA, MANOVA, Mann-Whitney U, Kruskal-Wallis, chi-square, Fisher's exact — with proper assumption testing, effect sizes, and post-hoc analysis.
Pearson, Spearman, and Kendall correlations; simple and multiple linear regression; logistic regression (binary, multinomial, ordinal); stepwise regression — with full assumption diagnostics.
Full SEM, path analysis, and confirmatory factor analysis using AMOS, SmartPLS, or R lavaan. Mediation and moderation analysis, model fit indices (CFI, RMSEA, TLI, SRMR), and model comparison.
Kaplan-Meier survival curves, Cox proportional hazards regression, ROC curves with AUC, sensitivity/specificity, NNT, NNH, diagnostic accuracy statistics, and clinical epidemiology measures.
ARIMA, SARIMA, exponential smoothing, VAR models, Granger causality, unit root testing (ADF, PP), cointegration analysis — for economics, business, and environmental research.
Cronbach's alpha, McDonald's omega, item-total correlation, factor analysis (EFA and CFA), convergent and discriminant validity, average variance extracted (AVE) — essential for survey-based research.
Thematic analysis, content analysis, discourse analysis, grounded theory — using NVivo or Atlas.ti. Qualitative and mixed-methods research fully supported.
Most widely used in social science, medicine, and business research. Full analysis and publication-ready output.
Open-source statistical computing — preferred for advanced statistical modeling, bioinformatics, and reproducible research.
SciPy, statsmodels, pingouin — for data scientists and researchers needing code-based analysis pipelines.
IBM AMOS for Structural Equation Modelling, CFA, path analysis, and latent variable modeling.
Partial Least Squares SEM — popular in business, management, and IS research for PLS-SEM analysis.
Econometrics, panel data, survival analysis, and health economics — preferred in many medical and economic studies.
Biomedical and life science analysis — t-tests, ANOVA, survival, non-linear curve fitting.
Qualitative data analysis — thematic coding, content analysis, interview data, focus groups.
All statistical results presented in properly formatted tables matching your target journal's style — APA, Vancouver, AMA, or any other format required.
Charts, graphs, box plots, forest plots, survival curves — all generated at 300 DPI or higher in formats accepted by journals (TIF, EPS, PDF).
Every result is explained in clear, precise academic language — suitable for direct use in your paper's results and discussion sections. Findings are interpreted contextually, not just described.
SPSS syntax, R scripts, or Python notebooks provided so your analysis is fully reproducible and transparent for reviewers and future reference.
A comprehensive report covering all analysis steps, assumption checks, test results, and interpretation — useful for thesis appendices and methodological transparency.
1,000+ research studies supported. Share your data and research questions — we'll handle the rest.
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