The ChakataStat Tutorial Workbook
A ten-module course that teaches ChakataStat by doing, built for self-study
and for classroom training of students, teaching staff and researchers. Every
module works on the same bundled sample health study (600 synthetic
participants; see the codebook), so there is nothing to
download: File → Open Sample Dataset (Ctrl+Shift+O) and you are ready.
Each module has the same shape: a question a researcher would actually ask, the menu path that answers it, how to read the output, an exercise to do on your own, and (at the end) the syntax the module generated, because every GUI action in ChakataStat also records an editable, re-runnable command. By module 10 that trail is the star of the show.
If you have not run the app before, do the ten-minute Quick Start first; it previews modules 1–7 in one pass.
The modules
| # | Module | You learn |
|---|---|---|
| 1 | Opening data & the two Views | The sample dataset, Data vs Variable View, a CSV export→import round trip, and which formats keep the labels |
| 2 | The Variable View | Types, labels, value labels, missing codes, measures, and why they matter |
| 3 | Describing your data | Frequencies, Descriptives, Explore |
| 4 | Graphs | Histogram, Boxplot, the Chart Builder, editing a chart, and exporting one |
| 5 | Two categorical variables | Crosstabs and the chi-square test |
| 6 | Comparing group means | Independent/paired t tests, One-Way ANOVA |
| 7 | Relationships | Correlation, linear regression, and the diagnostics that check it |
| 8 | Making new variables | Compute Variable and Recode (grouping BMI into categories) |
| 9 | Missing data | Blanks vs declared missing codes; Missing Value Analysis |
| 10 | Reproducibility | The Syntax editor, .cks scripts, exporting output |
For instructors
- Modules are 20–40 minutes each including the exercise; 1–5 make a half-day introductory session, 6–10 a second session.
- The dataset's structure is planted and documented: the codebook lists which effects are real, and which relationships are deliberately null so students also experience a non-significant result. Answers to each exercise are therefore checkable.
- The sample always opens as a new, unsaved document: students can never
damage it, and a fresh copy is one
Ctrl+Shift+Oaway. - The data are synthetic. No statistic derived from them describes any real population; they exist so the methods can be taught.