sampled

简明释义

英[ˈsæmpld]美[ˈsæmpəld]

v. 抽取……的试样；品尝，体验；节录，选录（sample 的过去式和过去分词）

英英释义

单词用法

同义词

反义词

例句

1.They sampled bacteria from nine computer mice and from the nine mouse owners.

他们分别对九个电脑鼠标和九个电脑鼠标拥有者的手指进行了细菌采样。

2.The goods have sampled out.

这些货物已抽样验收过了。

3.Fixed number of users: The number that you select is sampled from each user group.

Fixednumberofusers：您在每个用户组中选择的作为样本的用户数。

4.We sampled a selection of different bottled waters.

我们品尝了挑选出来的各种瓶装水。

5.I sampled the delights of Greek cooking for the first time.

我第一次品尝到希腊烹饪的美味。

6.12% of the children sampled said they prefer cats to dogs.

在被抽样调查的孩子中，12%说他们喜欢猫胜过喜欢狗。

7.System page-level sampling is similar to row-level sampling, except that the pages are sampled and not rows.

系统页级抽样与行级抽样类似，除了抽样的对象是页面而不是行。

8.The researchers sampled a group of participants for their study.

研究人员对他们的研究对象进行了抽样。

9.At the festival, we sampled various types of food from different vendors.

在节日上，我们从不同的摊贩那里品尝了各种食物。

10.The company sampled its products to gather customer feedback.

公司对其产品进行了抽样以收集客户反馈。

11.In the lab, scientists sampled water from the river to test for pollutants.

在实验室，科学家从河中取样水以检测污染物。

12.During the tasting event, guests sampled wines from local vineyards.

在品酒活动中，客人们品尝了来自当地葡萄园的葡萄酒。

作文

In the realm of scientific research, the concept of sampling is fundamental to drawing conclusions about a population. When researchers want to understand the characteristics of a large group, they often cannot study every single member due to time, cost, or logistical constraints. Instead, they select a smaller subset of the population to analyze. This smaller group is referred to as a sample. For instance, if a scientist is interested in studying the eating habits of teenagers in a large city, it would be impractical to observe every teenager. Therefore, the researcher might choose to focus on a specific number of individuals who represent the larger group. In this process, the teenagers are sampled (抽样) from various neighborhoods and backgrounds to ensure diversity in the data collected. The reliability of the results obtained from a sample largely depends on how well the sample represents the entire population. If the sample is biased or too small, the conclusions drawn may not accurately reflect the reality of the larger group. To mitigate these risks, researchers often employ various sampling techniques. Random sampling, for example, involves selecting individuals from the population at random, which helps to eliminate bias and ensures that every individual has an equal chance of being included in the study. In our earlier example, if the researcher randomly sampled (抽样) teenagers from different schools across the city, the findings would likely provide a more accurate picture of overall eating habits among teenagers. Another important aspect of sampling is the size of the sample itself. A larger sample size generally leads to more reliable results because it reduces the margin of error. However, larger samples also require more resources and time to analyze. Researchers must strike a balance between having a sufficiently large sample and managing their available resources effectively. In some cases, pilot studies are conducted where a smaller sample is initially sampled (抽样) to test the feasibility of the research design before proceeding with a larger study. Moreover, the concept of sampling is not limited to scientific research; it is prevalent in various fields such as marketing, social sciences, and even politics. For example, polling organizations often sampled (抽样) a portion of the electorate to predict the outcome of an election. By analyzing the opinions of a carefully selected group of voters, they can make informed estimates about the preferences of the larger population. However, these polls can only be as accurate as the methods used to select the individuals who are sampled (抽样). If the sample does not accurately reflect the demographics of the entire voting population, the predictions may be flawed. In conclusion, the act of sampling plays a crucial role in research and data analysis across various disciplines. Whether scientists, marketers, or political analysts are involved, the process of selecting a representative sample allows them to gain insights and make informed decisions without needing to engage with every individual in a population. Understanding how to effectively sample (抽样) is essential for anyone looking to draw meaningful conclusions from their data. As we continue to navigate an increasingly data-driven world, the importance of proper sampling techniques will only grow, highlighting the need for rigorous standards and practices in research methodologies.

在科学研究领域，抽样的概念对于得出关于一个群体的结论是至关重要的。当研究人员想要了解一个大群体的特征时，由于时间、成本或后勤限制，他们通常无法研究每一个成员。相反，他们会选择一个较小的子集进行分析。这个较小的群体被称为样本。例如，如果一位科学家对研究一个大城市青少年的饮食习惯感兴趣，观察每个青少年将是不切实际的。因此，研究人员可能会选择关注一些代表更大群体的个体。在这个过程中，这些青少年被从各个社区和背景中抽样（sampled）以确保收集数据的多样性。 从样本中获得的结果的可靠性在很大程度上取决于样本是否能够很好地代表整个群体。如果样本存在偏差或者样本量太小，则得出的结论可能无法准确反映更大群体的现实。为了降低这些风险，研究人员通常采用各种抽样技术。例如，随机抽样涉及从总体中随机选择个体，这有助于消除偏见，并确保每个个体都有相等的机会被纳入研究。在我们之前的例子中，如果研究人员随机抽样（sampled）来自城市不同学校的青少年，研究结果可能会更准确地反映青少年整体的饮食习惯。 抽样的另一个重要方面是样本的大小。较大的样本量通常会导致更可靠的结果，因为它减少了误差范围。然而，较大的样本也需要更多的资源和时间来分析。研究人员必须在拥有足够大的样本和有效管理可用资源之间找到平衡。在某些情况下，会进行初步研究，其中最初从较小的样本中抽样（sampled），以测试研究设计的可行性，然后再进行更大规模的研究。 此外，抽样的概念不仅限于科学研究；它在市场营销、社会科学甚至政治等各个领域都很普遍。例如，民意调查机构经常抽样（sampled）选民中的一部分，以预测选举结果。通过分析经过精心选择的选民群体的意见，他们可以对更大群体的偏好做出知情的估计。然而，这些民调的准确性只能与用于选择被抽样（sampled）个体的方法一样。如果样本没有准确反映整个选民群体的人口统计特征，预测可能会出现错误。 总之，抽样行为在各个学科的研究和数据分析中发挥着至关重要的作用。无论是科学家、市场营销人员还是政治分析师，选择一个具有代表性的样本使他们能够获得洞察力并做出明智的决策，而不需要与群体中的每一个个体接触。理解如何有效地抽样（sample）对于任何希望从其数据中得出有意义结论的人来说都是必不可少的。随着我们继续在一个越来越依赖数据的世界中航行，适当抽样技术的重要性只会增加，突显出研究方法中严格标准和实践的必要性。