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Econometric Views (EViews)01:29

Econometric Views (EViews)

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...
Time-Series Graph00:54

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
Qualitative Analysis03:46

Qualitative Analysis

For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
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Qualitative Analysis

Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
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Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
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Related Experiment Video

Updated: Jul 4, 2026

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

Stakeholder perspectives on implementing ED time series forecasting: a qualitative interview study.

Luka Petravić1,2, Kaja Gril Rogina3,4, Janez Žibert4,5

  • 1Department of Endocrinology and Diabetology, UKC Maribor, Ljubljanska ulica 5, Maribor, 2000, Slovenia. lpetravic@me.com.

BMC Emergency Medicine
|July 3, 2026
PubMed
Summary
This summary is machine-generated.

Time series forecasting (TSF) can help emergency departments (EDs) manage patient flow and staffing. This study explored ED directors' views on TSF, identifying new variables and recommending practical implementation strategies for better clinical integration.

Keywords:
BoardingDecision support systemEmergency department directorsEmergency departmentsEuropeInterview studyOvercrowdingPersonnel staffing and schedulingTime seriesTime series forecastingTranslational science

Related Experiment Videos

Last Updated: Jul 4, 2026

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

Area of Science:

  • Healthcare Management
  • Data Science in Medicine
  • Operations Research

Background:

  • Emergency departments face increasing patient volumes and staffing shortages, challenging resource management.
  • Time series forecasting (TSF) offers a statistical approach to predict future trends using historical data.
  • Bridging the gap between TSF research and practical emergency care application is crucial.

Purpose of the Study:

  • To explore the practical applicability of time series forecasting in everyday emergency department settings.
  • To understand European emergency department directors' perspectives on adopting TSF.
  • To identify barriers and facilitators for integrating TSF into clinical practice.

Main Methods:

  • Prospective qualitative interview study design.
  • Conducted semi-structured interviews with 26 European emergency department directors across 19 countries.
  • Analysis followed Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines.

Main Results:

  • Over 50% of interviewed directors had prior knowledge of TSF.
  • TSF is currently implemented in daily practice in only three countries.
  • Directors are open to data-informed decision support tools, and new external variables (e.g., primary care availability, neighboring hospital status) were identified.

Conclusions:

  • Future TSF models for EDs should include short- and long-term forecast horizons.
  • In-depth interviews with local staff are essential for aligning TSF models with operational needs.
  • Validating TSF models with real-world data and focusing on usability will enhance translation from research to practice.