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Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

181
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
181
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

131
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
131
Econometric Views (EViews)01:29

Econometric Views (EViews)

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Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
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Statgraphics01:10

Statgraphics

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Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
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Introduction to R01:11

Introduction to R

291
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
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Overview of Minitab01:11

Overview of Minitab

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Minitab is a statistical software package designed for data analysis. With its origins in the 1970s and development at Pennsylvania State University, Minitab has grown significantly in its capabilities and applications. It plays a crucial role in quality management projects, especially in Six Sigma initiatives, by offering tools for process improvement and statistical analysis. Minitab's significance lies in its user-friendly interface, making complex statistical analysis accessible to...
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Updated: Jul 8, 2025

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
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业务预测方法:令人印象深刻的进展,落后的实施.

Paul Goodwin1, Jim Hoover2, Spyros Makridakis3

  • 1School of Management, University of Bath, Bath, United Kingdom.

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概括
此摘要是机器生成的。

组织可以通过先进的预测方法来改善决策,但许多组织未能采用这些方法. 本研究探讨了采用率低的原因,并提出了更广泛使用系统预测的途径.

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科学领域:

  • 运营研究 运营研究
  • 业务分析 业务分析
  • 管理科学 管理科学

背景情况:

  • 准确的预测对于各种行业的运营和财务业绩至关重要.
  • 最近预测方法的进步为提高准确性提供了显著的潜力.
  • 尽管有好处,但许多组织没有采用系统的预测实践.

研究的目的:

  • 提供最近预测技术进步的概述.
  • 调查系统预测方法采用率较低背后的原因.
  • 确定促进更广泛使用先进预测的战略.

主要方法:

  • 对近期预测进步的文献综述.
  • 分析使用预测的组织调查数据的分析.
  • 与预测专业人士进行深入的半结构化采访.

主要成果:

  • 组织面临的障碍是采用先进的预测方法.
  • 缺乏意识,感知复杂性和资源不足阻碍了采用.
  • 特定的组织和技术因素影响了新预测工具的采用.

结论:

  • 尽管有证实的好处,但系统预测的采用仍然很低.
  • 解决已识别的障碍对于增加先进预测的使用至关重要.
  • 实施有针对性的战略可以促进更广泛的采用,并提高组织绩效.