Statistical analysis
without the setup hell
Tell your AI assistant what test you need. MCP Analytics runs the correct statistical model on your data and returns a complete report — with interpretation, charts, and p-values. No R setup, no SPSS license, no Stack Overflow rabbit holes.
ML models
to get started
with peer-reviewed packages
papers & presentations
Parametric & Non-Parametric Tests
The core tests you'll need for any research methods course, thesis, or dissertation. Each report includes test statistic, p-value, effect size, and written interpretation.
Independent Samples t-test
Compare means between two groups. Returns t-statistic, degrees of freedom, p-value, Cohen's d, and confidence interval with plain-English interpretation.
One-Way ANOVA
Test for differences across three or more groups. Includes F-statistic, post-hoc Tukey comparisons, and effect size (η²) with assumption checks.
ANCOVA
Analysis of covariance — compare group means while controlling for a continuous covariate. Removes confounders that ANOVA can't account for.
Chi-Square Test
Test independence between two categorical variables. Returns χ² statistic, degrees of freedom, p-value, Cramér's V effect size, and contingency table visualization.
Mann-Whitney U Test
Non-parametric alternative to the t-test when normality can't be assumed. Rank-based comparison with effect size r and bootstrapped confidence intervals.
Kruskal-Wallis Test
Non-parametric ANOVA alternative. Compares medians across 3+ groups with Dunn's post-hoc testing and effect size η²H.
Predictive Modeling
From simple linear regression to regularized models to classification — fully interpreted outputs with diagnostic plots, coefficients, and model fit statistics.
Linear Regression
Ordinary least squares with coefficient table, R², F-statistic, residual diagnostics, and multicollinearity checks (VIF). Full model summary.
Lasso Regression
L1 regularization for automatic feature selection. Cross-validated λ selection, coefficient shrinkage plot, and sparse model interpretation.
Ridge Regression
L2 regularization for multicollinear predictors. Shrinks coefficients toward zero without eliminating them, with optimal λ via cross-validation.
Logistic Regression
Binary or multiclass classification with odds ratios, ROC curve, AUC, confusion matrix, and probability calibration plots.
Naïve Bayes
Probabilistic classifier with feature independence assumption. Posterior probabilities, feature importance, and classification accuracy report.
Random Forest
Ensemble decision trees with variable importance, partial dependence plots, OOB error estimates, and tuning parameter selection.
Dimensionality Reduction & Unsupervised Learning
Explore structure in complex datasets. PCA, clustering, and correlation analysis for survey data, experimental results, and exploratory research.
Principal Component Analysis
PCA with scree plot, component loadings, biplot, and cumulative variance explained. Determine how many components to retain using Kaiser criterion and parallel analysis.
K-Means Clustering
Partition data into k groups with silhouette analysis for optimal k selection. Cluster profiles, within-cluster SS, and visualization plots.
DBSCAN Clustering
Density-based clustering that handles arbitrary shapes and noise. Identifies outliers as their own cluster — no need to pre-specify k.
Correlation Analysis
Full correlation matrix with Pearson, Spearman, or Kendall coefficients. Heatmap visualization, significance stars, and pairwise scatter plots.
Holm-Bonferroni Correction
Multiple comparisons correction to control family-wise error rate. Input your raw p-values and get adjusted values with interpretation of which results survive correction.
Intraclass Correlation (ICC)
Inter-rater reliability with ICC(2,1) and ICC(2,k) estimates. Agreement vs consistency distinction, confidence intervals, and Koo & Mae interpretation benchmarks.
Temporal Analysis
For longitudinal data, panel studies, and anything with a date column. Forecast future values or model time-to-event outcomes in survival studies.
ARIMA Forecasting
Auto-ARIMA with AIC-based order selection, ACF/PACF plots, residual diagnostics, and forecast with confidence bands. Industry-standard time series forecasting.
Prophet Decomposition
Trend + seasonality + holiday decomposition using Facebook's Prophet. Interpretable components, changepoint detection, and uncertainty intervals.
Cox Proportional Hazards
Survival regression modeling time-to-event outcomes with covariates. Hazard ratios, Kaplan-Meier curves, log-rank tests, and proportional hazards assumption diagnostics.
Trend Analysis
Moving averages, Mann-Kendall trend test, Sen's slope estimator, and trend line visualization. Detect significant monotonic trends in panel data.
XGBoost
Gradient boosting with hyperparameter tuning, SHAP feature importance, learning curves, and calibrated probability outputs.
Data Profiler
Automated EDA on any CSV — distributions, missing values, outliers, correlations, and data type recommendations. Start every analysis here.
Same statistics. Zero setup.
The math is identical to R, SPSS, and Python. The difference is how you get there.
- $99–$9,000/year license
- Desktop-only, heavy install
- Point-and-click menus, no reproducibility
- Output is a wall of tables, no interpretation
- No PDF export without manual copy-paste
- Hours of setup, version conflicts
- Learn syntax before you can run anything
- Debugging errors takes hours
- You write the interpretation yourself
- Free, reproducible, extensible
- Free to start, runs in your AI assistant
- No install — upload CSV, describe the test
- R-backed: same math, peer-reviewed packages
- AI-written interpretation included in every report
- One-click PDF export for papers & presentations
What students actually use it for
From intro statistics homework to PhD dissertation analysis — these are the workflows we see most.
Thesis / Dissertation Data Analysis
You've collected survey responses or experimental data. You need proper tests with effect sizes and assumption checks — formatted for a methods section.
Experimental Methods Coursework
Weekly problem sets requiring specific tests. Upload your data file, say what test you need, get the output with full workings — cite the method in your write-up.
Machine Learning Projects
Need to compare classifiers, validate a model, or demonstrate feature importance for a project? Get publication-ready outputs without writing a line of sklearn.
Economics & Finance Research
Time series, panel data, regression with controls — economics datasets need rigorous modeling. Get regression tables formatted like a journal paper.
Run your first test in 3 minutes
Upload your CSV, describe what you need, get a complete statistical report.
Free tier includes full access to all statistical tests. No credit card.