Statisticians
Computer and Mathematical Occupations- O*NET-SOC-Code
- 15-2041.00
Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide usable information. May specialize in fields such as biostatistics, agricultural statistics, business statistics, or economic statistics. Includes mathematical and survey statisticians.
Berufsbezeichnungen und Aufgabenbeschreibungen werden wie veröffentlicht auf Englisch angezeigt. Beschriftungen, einschließlich der Aufgabenarten, sind übersetzt.
KI-Exposition
- Datenquelle: BLSVeröffentlicht: 2026-08
Sehr hoch· relativ
NiedrigVier relative BänderSehr hochWert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)
831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band
- Datenquelle: AnthropicVeröffentlicht: 2026-03
0.211
0.000Spannweite der hier geführten Werte0.745Wert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Index der beobachteten Exposition, 0–1 wie veröffentlicht
Auf O*NET-Aufgaben abgebildet
Veröffentlicht je SOC-2018-Beruf; jeder O*NET-Beruf mit demselben SOC-2018-Code erhält diesen Wert
- Datenquelle: ILOVeröffentlicht: 2025
0.56
0.09Spannweite der hier geführten Werte0.70Wert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht
Veröffentlicht je ISCO-08-Berufsgattung. Mit diesem Beruf ganz oder teilweise verknüpft durch Anwendung der Umsteigeschlüssel des U.S. Bureau of Labor Statistics (ISCO-08 zu SOC 2010, SOC 2010 zu SOC 2018) in veröffentlichter Form
Welche Art von Wert diese Quelle veröffentlicht
Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.
KI-Exposition (OpenAI-Rubrik)
19 bewertete Aufgaben · 19 Aufgaben mit β ≥ 0,5 (100.0%)
β = direkte Exposition (E1) + 0,5 × Exposition bei verfügbaren Werkzeugen (E2), gemäß der Definition des Quell-Repositorys.
- Quelleinheit: Aufgaben aus O*NET 27.2 → Berufscode aus O*NET 31.0
- Alle bewerteten Aufgaben stehen in der Aufgabenliste von O*NET 31.0.
- Quelle
- OpenAI "GPTs are GPTs" exposure rubric
- Ausgabe
- gh-main-0471612
- Lizenz
- MIT License, Copyright (c) 2024 OpenAI
Aufgaben
Aufgabenbeschreibungen aus der O*NET® 31.0 Database, Kernaufgaben zuerst.
| Aufgabe | Art | β (OpenAI) |
|---|---|---|
| Report results of statistical analyses, including information in the form of graphs, charts, and tables. | Kern | 0,5 |
| Process large amounts of data for statistical modeling and graphic analysis, using computers. | Kern | 1 |
| Identify relationships and trends in data, as well as any factors that could affect the results of research. | Kern | 0,5 |
| Analyze and interpret statistical data to identify significant differences in relationships among sources of information. | Kern | 0,5 |
| Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data. | Kern | 1 |
| Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy. | Kern | 1 |
| Evaluate sources of information to determine any limitations, in terms of reliability or usability. | Kern | 0,5 |
| Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used. | Kern | 0,5 |
| Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses. | Kern | 0,5 |
| Supervise and provide instructions for workers collecting and tabulating data. | Kern | 1 |
| Apply sampling techniques, or use complete enumeration bases to determine and define groups to be surveyed. | Kern | 0,5 |
| Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering. | Kern | 1 |
| Develop and test experimental designs, sampling techniques, and analytical methods. | Kern | 1 |
| Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data. | Kern | 1 |
| Report results of statistical analyses in peer-reviewed papers and technical manuals. | Kern | 0,5 |
| Develop software applications or programming for statistical modeling and graphic analysis. | Kern | 1 |
| Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students. | Kern | 1 |
| Determine whether statistical methods are appropriate, based on user needs or research questions of interest. | Kern | 1 |
| Prepare and structure data warehouses for storing data. | Ergänzend | 1 |
Berufsinformationen
Quellen und Namensnennung
This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.
Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.
O*NET OnLine: 15-2041.00 Statisticians
KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.