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Data Collection by Observations01:08

Data Collection by Observations

11.9K
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...
11.9K
Quartile01:15

Quartile

4.2K
Quartiles are numbers that separate the data into quarters. Quartiles may or may not be part of the data. To find the quartiles, first, find the median or second quartile. The first quartile, Q1, is the middle value of the lower half of the data, and the third quartile, Q3, is the middle value, or median, of the upper half of the data. To get the idea, consider the same data set:
1; 1; 2; 2; 4; 6; 6.8; 7.2; 8; 8.3; 9; 10; 10; 11.5
The median or second quartile is seven. The lower half of the...
4.2K
Data Collection II01:29

Data Collection II

8.1K
The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
8.1K
Data Collection I01:30

Data Collection I

6.2K
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...
6.2K
Cluster Sampling Method01:20

Cluster Sampling Method

11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K
Histogram01:05

Histogram

12.9K
The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
12.9K

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相关实验视频

Updated: Jun 25, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

在Cuby框架中使用基准数据集进行工作.

Jan Řezáč1, Outi Vilhelmiina Kontkanen1, Martin Nováček1

  • 1Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.

The Journal of chemical physics
|May 22, 2024
PubMed
概括

库比框架通过提供有效的数据集管理和与各种软件集成的工具来简化计算化学. 它支持高级工作流程,并包括用于方法开发的新基准数据库.

科学领域:

  • 计算化学计算化学
  • 数据科学在化学中的数据科学

背景情况:

  • 计算化学方法开发需要强大的基准数据集进行验证.
  • 这些数据集的规模和数量不断增加,需要高效的数据处理工具.

研究的目的:

  • 审查Cuby框架用于管理计算化学基准数据集的功能.
  • 展示用于大规模计算和数据再利用的高级工作流程.
  • 为突出Cuby内部新基准数据库的整合.

主要方法:

  • 审查Cuby框架用于数据集操纵的功能.
  • 使用Cuby的高级计算工作流程的例子.
  • 集成和使用NCIAtlas和GMTKN55基准数据库.

主要成果:

  • Cuby提供了用于处理计算化学数据集的全面工具.
  • 该框架支持高性能计算资源上的大规模计算的高效处理.
  • Cuby促进了以前计算的数据的重复使用,提高了工作流的效率.
  • 现在可以通过Cuby访问NCIAtlas和GMTKN55数据库.

结论:

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  • 对于计算化学家来说,Cuby是一个有价值的框架,它可以有效地管理和利用基准数据.
  • 它的高级功能和数据库集成支持计算化学方法的开发和验证.