Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.

“Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.” is a core task performed by Statisticians. Among the occupation's 19 rated tasks, workers place it 10th by importance (#10 most important). About 100% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Analyze scientific or applied data using mathematical principles. in Analyzing Data or Information

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E1. Direct exposure — a language model could plausibly cut the time to do this task by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 1.00. Automation potential label: T2.

Other tasks in this occupation

• Analyze and interpret statistical data to identify significant differences in relationships among sources of information. · importance 4.7
• Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy. · importance 4.7
• Report results of statistical analyses, including information in the form of graphs, charts, and tables. · importance 4.5
• Determine whether statistical methods are appropriate, based on user needs or research questions of interest. · importance 4.5
• Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data. · importance 4.5
• Develop and test experimental designs, sampling techniques, and analytical methods. · importance 4.4
• Identify relationships and trends in data, as well as any factors that could affect the results of research. · importance 4.3
• Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students. · importance 4.3
• Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses. · importance 4.3
• Evaluate sources of information to determine any limitations, in terms of reliability or usability. · importance 4.1
• Process large amounts of data for statistical modeling and graphic analysis, using computers. · importance 4.0
• Develop software applications or programming for statistical modeling and graphic analysis. · importance 3.9
• Report results of statistical analyses in peer-reviewed papers and technical manuals. · importance 3.9
• Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used. · importance 3.8

See all tasks on the Statisticians page.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-8965,
  title  = {Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-8965}
}