Descriptive stats, frequency tables, charts & probability distributions — all in your browser. Download Python, R & Stata scripts to verify your results.
Enter your data and click Analyse to see descriptive statistics
Enter your data and click Analyse to see the frequency table
Uses the data from the left panel as your time series (Y values, chronological order). Optionally enter period labels below.
Enter data as 4 columns: Entity, Time, Y, X (comma/tab separated, one row per line). Header row is ignored if non-numeric.
Paste a single column of data below, apply a transformation, and copy the result into any analysis.
Enter X and Y values (one per line or comma-separated). Counts must match.
Enter Y and multiple X values (one per line or comma-separated). All counts must match.
Tests whether the population mean equals a hypothesised value μ₀ (uses data from left panel).
Tests whether two independent groups have equal means.
Enter observed counts. Leave expected blank for equal distribution.
If you use this calculator in your research or academic work, please cite it using one of the formats below. The access date is automatically set to today.
Generates APA 7th-edition formatted results paragraphs and tables for each analysis you have run. Click Generate Report after running your analyses.
Only sections where you have run an analysis will appear. Variable names labelled as X and Y — replace with your actual variable names in the final manuscript.
No analyses run yet.
Go to any analysis tab, run a calculation, then return here and click Generate Report.
Enter Y (dependent) and X (independent) time series. ARDL models the dynamic relationship with lagged Y and X. Used for the Pesaran, Shin & Smith (2001) bounds cointegration test.
Paste a return series or residuals. Estimates time-varying conditional variance. ARCH(q): Engle (1982). GARCH(1,1): Bollerslev (1986).
A comprehensive, offline-capable statistical calculator designed for researchers, students, and professionals. It covers descriptive statistics, hypothesis testing, regression, time series, panel data, ARDL, ARCH/GARCH, and research-paper-ready report generation — all in one place.
.txt.| Format | Example | Used in |
|---|---|---|
| Comma-separated | 23, 45, 67, 12, 34 | All single-variable tabs |
| One per line | 23 45 67 | All single-variable tabs |
| Two columns (X and Y) | X field: 1,2,3 Y field: 4,5,6 | Regression, Hypothesis |
| Multi-column matrix | 2, 25, 2 3, 26, 2 5, 30, 3 | Multiple Regression, Panel Data |
| Panel data (entity, time, Y, X) | 1, 1, 45, 3.2 1, 2, 48, 3.5 | Panel Data tab |
Use Sample Data buttons in each tab to auto-fill a working example.
| Tab | What it does | Key output |
|---|---|---|
| Descriptive | Core summary statistics for any dataset | Mean, median, SD, skewness, kurtosis, quartiles, outlier detection |
| Frequency | Frequency tables for raw or grouped data | Frequency, relative %, cumulative % |
| Charts | Visual plots of your data | Histogram, box plot, line chart, bar chart — all downloadable |
| Time Series | Time series analysis with unit root and autocorrelation tests | ADF, KPSS, PP, Ljung-Box, ARCH-LM, ACF/PACF, SMA/EMA, decomposition, RMSE/MAE/MAPE |
| Panel Data | Multi-entity panel regression estimators | Pooled OLS, Fixed Effects, First Differences, Between, Hausman test, Pesaran CD, LLC/IPS |
| Regression | Simple and multiple OLS regression with diagnostics | β̂, SE, t, p, R², Adj. R², F-stat, VIF, scatter/residual plots; Data Transformer (lag, log, diff, sqrt…) |
| Hypothesis | Inferential tests for means and distributions | One-sample t, Welch two-sample t, Chi-square goodness-of-fit |
| Probability | Distribution calculators | Normal, t, Chi-square, F, Binomial, Poisson probabilities and critical values |
| Adv. TS | Advanced time series models | ARDL(p,q) with Pesaran bounds test + long-run coefficients; ARCH(q) + GARCH(1,1) with conditional volatility chart |
| Report | APA 7th edition research paper output | Auto-generates formatted results paragraphs and tables for every analysis you run — copy or download |
| Cite | Citation generator for the calculator | APA, MLA, Chicago, IEEE reference formats |
Found in the Regression tab. Paste any column of numbers and apply a transformation before using it in regression or time-series analysis.
| Transform | Formula | When to use |
|---|---|---|
| Lag(k) | Yt-k | Autoregressive models, Granger causality, ARDL |
| Δ¹ First difference | Yt − Yt-1 | Remove linear trend, stationarise I(1) series |
| ln(x) | loge(x) | Reduce right skew, log-linear models, elasticities |
| log₁₀(x) | log10(x) | Orders-of-magnitude scaling |
| √x | x0.5 | Moderate right skew, count data |
| x² | x × x | Quadratic relationship in regression |
| 1/x | x−1 | Reciprocal models, convergence models |
| Term | Meaning |
|---|---|
| ADF | Augmented Dickey-Fuller test — tests if a time series has a unit root (i.e., is non-stationary) |
| KPSS | Kwiatkowski-Phillips-Schmidt-Shin test — null is stationarity (opposite of ADF) |
| ARDL | AutoRegressive Distributed Lag — models relationship between Y and lagged values of Y and X |
| Bounds Test | Pesaran (2001) F-test for cointegration regardless of whether variables are I(0) or I(1) |
| ARCH/GARCH | Models for time-varying volatility — essential for financial return series |
| VIF | Variance Inflation Factor — measures multicollinearity among predictors in regression |
| ECM | Error Correction Model — shows speed of adjustment back to long-run equilibrium |
| Hausman Test | Panel data test to choose between Fixed Effects and Random Effects estimators |
| Pesaran CD | Cross-Sectional Dependence test for panel data — important for macro panels |
| Ljung-Box Q | Tests for autocorrelation in residuals — if significant, model is mis-specified |
Developed by Tech Bridge Innovations (TBI) — techbridgeinn.com
All statistical computations run entirely in your browser using JavaScript.
No data is transmitted, stored, or shared. Your privacy is fully protected.
For academic use, please cite using the Cite tab.
Run your analyses first, then click Generate Scripts to get ready-to-run code for Python, R, Stata, and EViews — covering all analyses performed in this session.
Scripts use your actual data values (up to 100 obs) or placeholder variable names for larger datasets.
Run any analysis first, then click Generate Scripts above.