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相关概念视频

Data Collection I01:30

Data Collection I

6.0K
Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
6.0K
Data Collection by Observations01:08

Data Collection by Observations

11.7K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Review and Preview01:13

Review and Preview

8.8K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
8.8K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

31.5K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
31.5K
Data Collection III01:05

Data Collection III

2.6K
The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the...
2.6K
Data Collection by Survey01:07

Data Collection by Survey

6.4K
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...
6.4K

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相关实验视频

Updated: May 24, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

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2. 2. 2. 这是一个很棒的节目. 数据类型和数据整理,以实现高效的处理.

A Indrayan1

  • 1Department of Clinical Research, Max Healthcare, New Delhi, India.

Journal of postgraduate medicine
|March 6, 2025
PubMed
概括
此摘要是机器生成的。

适当的数据整理和理解数据类型对于研究中准确的统计分析至关重要. 本指南有助于研究人员,特别是职业生涯早期的科学家,有效地管理数据以得出可靠的结论.

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科学领域:

  • 实证研究方法学 实证研究方法学
  • 生物统计学和数据分析

背景情况:

  • 数据收集和对比是实证研究的基础.
  • 统计分析依赖于适当整理的数据,方法因数据类型而异.
  • 研究人员,特别是职业生涯早期的科学家,经常需要有关数据管理和呈现的指导.

研究的目的:

  • 阐明各种数据类型及其适当的统计分析.
  • 为有效的数据通信提供准备表格和图形的指导.
  • 提高研究生,年轻研究人员和经验丰富的专业人员的数据管理技能.

主要方法:

  • 数据类型的审查,包括定量,定性和顺序数据.
  • 解释数据整理技术和最佳实践.
  • 在研究报告中有效使用表格和图形的指导.

主要成果:

  • 了解不同类型的数据对于适当的统计处理至关重要.
  • 有效的数据整理确保了研究结果的完整性.
  • 审慎使用表格和图形显著改善了结果的沟通.

结论:

  • 从收集到呈现,准确的数据管理对于在经验研究中得出正确的结论至关重要.
  • 这篇文章是所有职业阶段的研究人员的实用资源,以提高他们的数据处理和报告能力.