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Stata (/ˈsteɪtə/, STAY-ta, alternatively /ˈstætə/, occasionally stylized as STATA) is a general-purpose statistical software package developed by StataCorp for data manipulation, visualization, statistics, and automated reporting. It is used by researchers in many fields, including biomedicine, economics, epidemiology, and sociology.
The analysis highlights History, Technical overview and terminology and Software products as prominent areas in the source structure around Stata.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Stata shows recurring relationship patterns in the source. For example, Stata → All Stata, Bill, Gould, In, Linux, MacOS, MicroTSP, MS-DOS, Sean Becketti, Since, Support Disks, SYSTAT, The, There, Unix, William, Windows, With, Written Another extracted example is Stata → Bittmann, Boston, Cengage, College Station, DeGruyter Oldenbourg, Enrique, Felix, Hamilton, ISBN, Lawrence, Pinzon, Really Short Introduction, Retrospective, Stata Press, Statistics, Texas, Thirty Years. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
commands data version user statacorp released statistical format release software se 1985 dataset formats users mp statistics including new technical
TTTA extracted 102 structured relationships around Stata. Examples in this analysis include Stata → Developer → StataCorp and Stata → License → Proprietary. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Stata | Developer | StataCorp | 1.00 | infobox |
| Stata | License | Proprietary | 1.00 | infobox |
| Stata | Operating system | Windows, macOS, Linux | 1.00 | infobox |
| Stata | Original author | William Gould | 1.00 | infobox |
| Stata | Release | 1985 (1985) | 1.00 | infobox |
| Stata | Stable release | 19.0 / April 8, 2025; 16 months ago (2025-04-08) | 1.00 | infobox |
| Stata | Type | Statistical analysis Numerical analysis | 1.00 | infobox |
| Stata | Website | www.stata.com | 1.00 | infobox |
| Stata | Written in | C | 1.00 | infobox |
| SYSTAT | instance of | The software was intended to compete with statistical programs for personal computers | 0.80 | text |
| MicroTSP | instance of | The software was intended to compete with statistical programs for personal computers | 0.80 | text |
| Stata | related to Data format compatibility | This | 0.60 | section |
The concept neighborhoods around Stata bring nearby vocabulary together. In this analysis, examples include Commands, Mp and Release. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Stata, one of the stronger structural bridges in this analysis connects Stata with Technical overview and terminology. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Stata to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Technical overview and terminology & Software products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Stata · EN edition · Analysis: TopicsToTalkAbout