Quick Start

From install to your first result in about ten minutes — one linear pass, no choices to make. Every step names the exact menu item.

1. Install and launch

• Windows — install ChakataStat from the Microsoft Store and launch it from the Start menu.
• Ubuntu / Linux — snap install chakatastat, then launch ChakataStat from your applications.

You land in the Data View: an empty spreadsheet-style editor (cases are rows, variables columns), with the menu bar above and the AI assistant panel on the right — ignore that panel for now (Ctrl+Shift+A hides it).

2. Open the sample dataset

File → Open Sample Dataset (Ctrl+Shift+O) loads the bundled teaching dataset: a synthetic health study of 600 participants and 21 variables — age, sex, blood pressure, glucose, cholesterol, smoking and more. It opens as a new, unsaved document, so nothing you do can damage the sample.

3. Read the two views

• Data View — the values, one row per participant. Click any cell and its whole row and column tint, so you can trace a case across the sheet.
• Variable View (Ctrl+2) — one row per variable: name, type, label, value labels (open EducationLevel's — codes 0–3 mean None/Primary/Secondary/Tertiary), declared missing values, and measure.

That metadata is what turns a grid of numbers into a dataset.

4. Run Frequencies on a categorical variable

Analyze → Descriptive Statistics → Frequencies… Move SmokingStatus into the Variables list, click Run. The app switches to the Output View with a frequency table: each category with its count and percent.

5. Run Descriptives on scale variables

Analyze → Descriptive Statistics → Descriptives… Move Age, BMI and SystolicBP across, Run — valid N, minimum, maximum, mean and standard deviation for each.

6. Compare two groups with a t test

Analyze → Compare Means → Independent-Samples T Test… Test variable SystolicBP, grouping variable Sex, Run. The output shows each group's mean and the test statistics; a small p value ("Sig.") means the difference is unlikely to be chance.

7. Draw a chart

Graphs → Histogram… (Ctrl+Shift+H), pick BMI, Run. A histogram card appears in the output right under your tables.

8. Keep your work

• File → Save (Ctrl+S) writes a .ckd document — data and every variable definition together.
• File → Export Output… writes the whole output log to HTML, Markdown or LaTeX.
• Switch to the Syntax tab: every step you took was also recorded as an editable, re-runnable command — that trail is how work in ChakataStat stays reproducible.

Where to go next

The full User Guide and a ten-module tutorial workbook (built on the same sample dataset, with exercises for classroom training) ship inside the app — press F1 or open Help → Documentation. Or ask the built-in AI assistant (Ctrl+Shift+A) for an analysis in plain language.