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STATCAL ONLINE • STATISTICAL METHODS

Analyze Data. Build Reliable Statistical Evidence.

A dedicated statistical analysis feature of STATCAL ONLINE.

STATCAL ONLINE Statistical Methods brings together focused, browser-based applications for regression, panel data analysis, hypothesis testing, group comparisons, questionnaire analysis, model diagnostics, reliability assessment, and other quantitative research workflows.

Statistical Analysis
Browser-Based
Research-Oriented
Exportable Results
STATCAL ONLINE Statistical Analysis Tools

Explore Statistical Methods

Select a statistical method based on your research design and analytical objective. Each application provides a focused workflow for data analysis, diagnostics, interpretation, and exportable statistical output.

Panel Data & Regression Models

Estimate and diagnose panel-data models, compare common, fixed, and random effects specifications, and analyze financial panel datasets.

1 Panel Data

Panel Data Regression Analyzer

Estimate Common Effect, Fixed Effect, and Random Effect models, compare specifications using Chow, Hausman, and Lagrange Multiplier tests, and export publication-ready panel regression results.

2 Panel Data

Random Effects GLS Panel Data Analyzer

Estimate Random Effect Models using random-effects GLS/FGLS, supported by model selection tests, regression diagnostics, interpretation, and exportable statistical output.

3 Fixed Effects

Panel Data Regression with Fixed Effects

Fit cross-section, period, or two-way fixed effects models with robust standard errors, fixed-effect intercepts, STATA-style within/between/overall R-squared, F tests, diagnostics, and exports.

4 Panel Financial Analysis

Panel Financial Descriptive, Correlation, and Regression Assumption Analyzer

Filter companies and years, calculate descriptive statistics, correlation matrices with p-values, estimate multiple regression, evaluate assumptions, and export tables or diagnostic graphics.

Regression & Questionnaire Analysis

Build multiple linear regression models, evaluate classical assumptions, work with questionnaire data, and inspect diagnostics and outliers.

5 Regression Diagnostics

Linear Regression Assumption Analyzer

Run multiple linear regression, classical assumption tests, outlier diagnostics, and publication-ready residual visualization for one dependent variable and multiple predictors.

6 Questionnaire Regression

Questionnaire Multiple Linear Regression and Classical Assumption Analyzer

Filter respondents, define categorical split groups, choose dependent and independent variables flexibly, estimate regression models, evaluate assumptions, and export scientific results.

Group Comparison & Experimental Analysis

Compare independent groups, paired measurements, or multiple groups using parametric and nonparametric procedures, effect sizes, diagnostics, and publication-ready graphics.

7 Two-Group Comparison

Independent Samples Analysis

Compare two independent groups using Student's t-test, Welch's t-test, Mann-Whitney U test, homogeneity testing, effect sizes, outlier diagnostics, split analysis, and flexible graphics.

8 Paired Comparison

Paired Samples Analysis

Analyze paired or repeated measurements using paired samples t-tests, Wilcoxon signed-rank tests, effect sizes, individual and group-level N-Gain, flexible graphics, and exportable results.

9 Multi-Group Comparison

One-Way ANOVA & Kruskal-Wallis Analysis

Compare two or more independent groups using classical ANOVA, Welch ANOVA, Kruskal-Wallis, multiple comparisons, post hoc tests, effect sizes, outlier diagnostics, and flexible graphics.

Measurement Quality

Evaluate questionnaire-item validity, internal consistency, item diagnostics, reverse coding, critical correlation values, and construct-level reliability.

10 Measurement Quality

Validity & Reliability Analysis

Evaluate Pearson and corrected item-total correlations, critical r values, Cronbach's alpha, alpha if item deleted, inter-item correlations, reverse-coded items, warnings, and diagnostics.

Click an application icon or the Open Application button to launch the corresponding STATCAL ONLINE statistical tool.
Statistical Analysis for Research & Learning

Designed for Practical Statistical Workflows

STATCAL ONLINE Statistical Methods focuses on helping users analyze, diagnose, interpret, and communicate quantitative evidence through focused browser-based applications.

Research Analyze data for theses, dissertations, journal manuscripts, institutional research, and professional studies.
Teaching Demonstrate statistical methods, model assumptions, diagnostics, and interpretation through interactive applications.
Diagnostics Examine model assumptions, outliers, homogeneity, normality, effect sizes, reliability, and other analytical evidence.
Reporting Export statistical tables, figures, and diagnostic outputs for academic and professional reporting.