sampled data

简明释义

取样数据

英英释义

例句

1.The survey was conducted on sampled data from various demographics.

调查是基于来自不同人群的抽样数据进行的。

2.To improve accuracy, the algorithm was tested with sampled data from previous experiments.

为了提高准确性，该算法使用了来自先前实验的抽样数据进行测试。

3.The company used sampled data to predict future sales trends.

公司使用抽样数据来预测未来的销售趋势。

4.By using sampled data, we can make inferences about the entire dataset.

通过使用抽样数据，我们可以对整个数据集做出推断。

5.The researchers collected sampled data to analyze the population's health trends.

研究人员收集了抽样数据以分析该人群的健康趋势。

作文

In the realm of data analysis, the term sampled data refers to a subset of data that is selected from a larger population for the purpose of statistical analysis. This process is crucial because it allows researchers and analysts to draw conclusions about a whole population without needing to examine every single data point. For instance, if a company wants to understand the purchasing habits of its customers, it may not be feasible to survey every customer. Instead, they can collect sampled data from a representative group of customers, which can provide insights into the broader customer base.The importance of sampled data cannot be overstated. It enables faster data collection and analysis, reduces costs, and minimizes the time required to gather information. By focusing on a smaller group, researchers can conduct more in-depth studies and analyses, which might be impossible with an overwhelming amount of data. Moreover, when done correctly, sampled data can yield results that are just as reliable as those obtained from analyzing the entire dataset.There are various methods for obtaining sampled data, including random sampling, stratified sampling, and systematic sampling. Random sampling involves selecting individuals randomly from the population, ensuring that each member has an equal chance of being chosen. Stratified sampling, on the other hand, divides the population into subgroups (or strata) and then samples from each subgroup. This method is particularly useful when certain characteristics need to be represented proportionally in the sample. Systematic sampling involves selecting every nth individual from a list of the population, which can also yield effective results if the list is organized appropriately.However, it is essential to recognize the potential pitfalls of using sampled data. If the sample is not representative of the larger population, the results can be skewed, leading to incorrect conclusions. For example, if a survey about public opinion on a new policy only includes responses from a specific demographic, such as young adults in urban areas, the findings may not accurately reflect the views of the entire population. Therefore, careful planning and execution of the sampling process are vital to ensure the validity of the results.In conclusion, sampled data plays a pivotal role in research and data analysis. It allows for efficient and cost-effective ways to gather insights about larger populations while still maintaining a level of accuracy and reliability. By employing various sampling methods and being mindful of the potential biases, researchers can harness the power of sampled data to inform decision-making and drive progress in various fields. As we continue to advance in the age of information, understanding and utilizing sampled data will remain a critical skill for analysts and researchers alike.

在数据分析领域，术语sampled data指的是从更大的人群中选择的一个数据子集，以进行统计分析。这个过程至关重要，因为它允许研究人员和分析师在不需要检查每一个数据点的情况下，对整个群体得出结论。例如，如果一家公司想要了解其客户的购买习惯，调查每位客户可能并不切实际。相反，他们可以从一个具有代表性的客户群体中收集sampled data，这可以为更广泛的客户基础提供见解。sampled data的重要性不可低估。它使数据收集和分析变得更快，降低了成本，并减少了收集信息所需的时间。通过专注于较小的群体，研究人员可以进行更深入的研究和分析，这在面对庞大的数据量时可能是不可能的。此外，当执行得当时，sampled data可以产生与分析整个数据集获得的结果同样可靠的结果。获取sampled data的方法有多种，包括随机抽样、分层抽样和系统抽样。随机抽样涉及从人群中随机选择个体，确保每个成员都有相等的被选中机会。而分层抽样则将人群划分为子组（或层），然后从每个子组中抽样。这种方法在需要按比例代表某些特征时特别有用。系统抽样则涉及从人群列表中每隔n个个体选择一个，这也可以产生有效的结果，前提是该列表组织得当。然而，重要的是要认识到使用sampled data的潜在陷阱。如果样本不代表更大的人群，结果可能会偏斜，从而导致错误的结论。例如，如果一项关于新政策的公众意见调查仅包括来自特定人口统计的回应，例如城市地区的年轻人，那么调查结果可能无法准确反映整个群体的观点。因此，仔细规划和执行抽样过程对于确保结果的有效性至关重要。总之，sampled data在研究和数据分析中发挥着关键作用。它为收集有关更大人群的见解提供了高效且具有成本效益的方法，同时仍保持一定程度的准确性和可靠性。通过采用各种抽样方法并注意潜在的偏见，研究人员可以利用sampled data的力量来支持决策和推动各个领域的进步。随着我们继续在信息时代前进，理解和利用sampled data将仍然是分析师和研究人员的重要技能。