ChakataStat
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Quick Start

From installing the app to your first result in about ten minutes. Each step names the exact menu item to use.

1. Install and open the app

  • Windows: install ChakataStat from the Microsoft Store and open it from the Start menu.
  • Ubuntu and other Linux: run snap install chakatastat, then open ChakataStat from your applications.

The app opens in the Data View, an empty spreadsheet where each row is a case and each column a variable. The menus are at the top and the AI assistant panel is on the right. You can hide the panel with Ctrl+Shift+A.

2. Open the sample dataset

Choose File → Open Sample Dataset (Ctrl+Shift+O). This loads a synthetic health study of 600 participants and 21 variables, including age, sex, blood pressure, glucose, cholesterol and smoking. It opens as a new, unsaved document, so you can't damage the original.

3. Look at the two views

  • Data View shows the values, one row per participant. Click a cell and its row and column are highlighted, which makes a case easy to follow across the sheet.
  • Variable View (Ctrl+2) shows one row per variable: its name, type, label, value labels, missing values and measurement level. Open the value labels of EducationLevel to see that codes 0 to 3 mean None, Primary, Secondary and Tertiary.

This information is what makes a grid of numbers into a dataset.

4. Run Frequencies on a categorical variable

Choose Analyze → Descriptive Statistics → Frequencies…, move SmokingStatus into the Variables list and click Run. The app switches to the Output View and shows a table with the count and percentage of each category.

5. Run Descriptives on numeric variables

Choose Analyze → Descriptive Statistics → Descriptives…, move Age, BMI and SystolicBP across and click Run. You get the number of valid cases, the minimum, maximum, mean and standard deviation of each.

6. Compare two groups with a t test

Choose Analyze → Compare Means → Independent-Samples T Test…. Use SystolicBP as the test variable and Sex as the grouping variable, then click Run. The output shows the mean of each group and the test results. A small p value (the "Sig." column) means a difference this large would be unlikely if both groups had the same population mean.

7. Draw a chart

Choose Graphs → Histogram… (Ctrl+Shift+H), pick BMI and click Run. The histogram appears in the output below your tables.

8. Keep your work

  • File → Save (Ctrl+S) writes a .ckd document with the data and every variable's settings.
  • File → Export Output… saves all the results as HTML, Markdown or LaTeX.
  • Open the Syntax tab to see every step you took, recorded as a command you can edit and run again. This is how you repeat an analysis later.

Where to go next

The full User Guide and a ten-part tutorial workbook, with exercises on the same sample dataset, are built into the app. Press F1 or choose Help → Documentation. You can also ask the AI assistant (Ctrl+Shift+A) to run an analysis for you in plain language.