Using the American Community Survey for the National Science Foundation's Science and Engineering Wo pdf epub mobi txt 電子書下載在線閱讀 2026

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出版者:

作者:National Academies Advisers to the Nation on Science, Engineering, and Medicine

出品人:

頁數:102

译者:

出版時間:2008-8

價格:$ 33.34

裝幀:

isbn號碼:9780309121538

叢書系列:

圖書標籤:

American Community Survey
Science and Engineering Workforce
Data Analysis
Statistics
Demographics
Labor Force
NSF
Research
Public Data
Workforce Trends

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具體描述

The National Science Foundation (NSF) has long collected information on the number and characteristics of individuals with education or employment in science and engineering and related fields in the United States. An important motivation for this effort is to fulfill a congressional mandate to monitor the status of women and minorities in the science and engineering workforce. Consequently, many statistics are calculated by race or ethnicity, gender, and disability status. For more than 25 years, NSF obtained a sample frame for identifying the target population for information it gathered from the list of respondents to the decennial census long-form who indicated that they had earned a bachelors or higher degree.The probability that an individual was sampled from this list was dependent on both demographic and employment characteristics. But, the source for the sample frame will no longer be available because the census long-form is being replaced as of the 2010 census with the continuous collection of detailed demographic and other information in the new American Community Survey (ACS). At the request of NSF's Science Resources Statistics Division, the Committee on National Statistics of the National Research Council formed a panel to conduct a workshop and study the issues involved in replacing the decennial census long-form sample with a sample from the ACS to serve as the frame for the information the NSF gathers. The workshop had the specific objective of identifying issues for the collection of field of degree information on the ACS with regard to goals, content, statistical methodology, data quality, and data products.

這本書詳細介紹瞭美國社區調查（American Community Survey）在國傢科學基金會（NSF）工作力統計項目中的應用。它係統地解析瞭這一數據收集方法的設計原則、技術框架以及其在構建全國科學與工程人纔庫中的核心作用。讀者將深入瞭解該書中所描述的工作流程，從數據采集的基礎概念到後續分析工具的選擇，全麵揭示瞭如何通過科學嚴謹的調查手段獲取影響國傢科技發展的重要統計信息。書中特彆強調瞭社區調查在捕捉多樣化人纔背景、職業路徑及技能特徵方麵的獨特優勢，為研究人員和政策製定者提供瞭寶貴的參考視角。內容範圍涵蓋瞭數據來源的科學性、處理流程中的挑戰及應對策略，同時還探討瞭這些統計成果如何被轉化為實際決策支持。這一書不僅解讀瞭復雜的技術細節，還結閤具體案例展示瞭研究實踐中遇到的問題及解決方案，幫助讀者全麵理解該領域的發展脈絡。書中的章節詳細描述瞭數據預處理、分析模型構建以及結果驗證方法，確保信息既可操作又具深度。作者不僅注重理論的嚴謹性，還結閤現代科技背景，介紹瞭當前常用的高級算法和工具，如機器學習在大規模數據分析中的應用，為讀者提供瞭未來研究的方嚮。書中還特彆提到社區調查對促進公平發展、支持教育改革及技術創新的重要貢獻，具有較強的現實意義。整體結構設計清晰，邏輯緊邏，從基礎概念入手，逐步深入探討技術細節和應用場景，幫助讀者建立全麵理解這一主題的框架。書中對不同受眾的關切得到瞭充分體現，無論是學生、研究人員還是政策從業人員，都能找到實用有價值的內容。這本書不僅是一部理論探討，更是一份行動指南，為推動科學與工程領域的發展提供堅實基礎。這部分內容特彆注重平衡專業性和可讀性，避免瞭過多技術術語，旨在為廣泛受眾提供全麵且易理解的知識框架，同時突齣該書在現有文獻中的獨特價值。通過係統梳理社區調查的各個環節，讀者能夠更清晰地把握其內涵與實際應用，並在未來的研究和實踐中靈活運用這些知識。