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Surveys02:16

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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
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Administrative and Survey Data: Potential and Pitfalls.

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Big data from administrative and survey sources offer broad insights but require careful interpretation for commercial, administrative, and clinical decisions. Caution is essential when drawing conclusions from these large datasets.

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Area of Science:

  • Health Informatics
  • Data Science in Healthcare

Background:

  • Large datasets, often termed "big data", are increasingly utilized for decision-making.
  • These data typically originate from administrative activities and surveys.
  • They offer a wider view of disease and care compared to traditional clinical experience or research.

Purpose of the Study:

  • To highlight the utility of big data in informing various decisions.
  • To emphasize the need for cautious inference when using big data.

Main Methods:

  • Analysis of data generated from administrative activities.
  • Review of survey data for decision-making insights.

Main Results:

  • Big data provides a broader perspective on disease and patient care.
  • Inferences drawn from big data necessitate careful consideration.

Conclusions:

  • While valuable, big data requires cautious interpretation for reliable decision-making.
  • The broad scope of big data complements, but does not replace, traditional research and clinical judgment.