sample interval

简明释义

抽样间隔取样间隔

英英释义

例句

1.Adjusting the sample interval 采样间隔 can help in identifying anomalies in the data.

调整 采样间隔 有助于识别数据中的异常情况。

2.We decided to use a one-week sample interval 采样间隔 for our survey to capture weekly trends.

我们决定使用一周的 采样间隔 来进行调查，以捕捉每周的趋势。

3.When measuring temperature, a shorter sample interval 采样间隔 can provide more detailed data.

在测量温度时，更短的 采样间隔 可以提供更详细的数据。

4.The sample interval 采样间隔 must be consistent to ensure valid comparisons across datasets.

为了确保数据集之间的有效比较，采样间隔 必须保持一致。

5.In statistical analysis, the choice of the sample interval 采样间隔 can significantly affect the results.

在统计分析中，采样间隔 的选择可以显著影响结果。

作文

In the field of statistics, understanding the concept of sample interval is crucial for conducting accurate research and analysis. A sample interval refers to the specific duration or range between data points that are selected from a larger population for the purpose of statistical sampling. This interval can significantly affect the results of any study or survey, as it determines how frequently data points are collected and analyzed. For example, in a survey measuring public opinion on a political issue, researchers might decide to collect responses every week for a month. In this case, the sample interval is one week. By choosing a shorter sample interval, the researchers can capture more dynamic changes in public opinion, but they may also face challenges such as respondent fatigue or a lower response rate. Conversely, if they opt for a longer sample interval, they might miss important fluctuations that occur within that period.The choice of sample interval is influenced by various factors, including the nature of the research question, the availability of resources, and the expected variability of the data. For instance, in studies where rapid changes are anticipated, such as in stock market analysis, a shorter sample interval is often necessary to provide timely insights. However, in more stable contexts, like demographic studies, researchers might choose a longer interval to reduce costs and simplify data collection.Furthermore, the implications of the sample interval extend beyond just data collection. The interval can also impact the statistical methods used for analysis. For example, time series analysis often requires careful consideration of the sample interval to ensure that trends and patterns are accurately identified. If the interval is too wide, important details may be overlooked; if it is too narrow, the data may become noisy and difficult to interpret.Researchers must also be aware of the potential biases introduced by their choice of sample interval. If the interval does not reflect the underlying characteristics of the population being studied, the results may be skewed. For example, if a survey is conducted only during weekdays, it may not accurately capture the opinions of individuals who work traditional hours and are unavailable to respond during that time.In conclusion, the sample interval is a fundamental aspect of statistical research that requires careful consideration. It influences not only the data collection process but also the validity and reliability of the research findings. By thoughtfully selecting an appropriate sample interval, researchers can enhance the quality of their studies and contribute valuable insights to their fields. Understanding this concept is essential for anyone engaged in data-driven decision-making, as it lays the groundwork for effective analysis and interpretation of results.

在统计学领域，理解样本间隔的概念对于进行准确的研究和分析至关重要。样本间隔是指从更大的人群中选择的数据点之间的特定持续时间或范围，其目的是进行统计抽样。这个间隔会显著影响任何研究或调查的结果，因为它决定了数据点收集和分析的频率。例如，在一项测量公众对政治问题看法的调查中，研究人员可能决定每周收集一次回应，持续一个月。在这种情况下，样本间隔为一周。通过选择较短的样本间隔，研究人员可以捕捉到公众意见中更动态的变化，但他们也可能面临诸如受访者疲劳或响应率降低等挑战。相反，如果他们选择较长的样本间隔，可能会错过在该期间内发生的重要波动。样本间隔的选择受到多种因素的影响，包括研究问题的性质、资源的可用性以及数据的预期变异性。例如，在预计快速变化的研究中，如股票市场分析，通常需要较短的样本间隔以提供及时的见解。然而，在更稳定的背景下，如人口统计研究，研究人员可能选择较长的间隔以降低成本并简化数据收集。此外，样本间隔的影响不仅限于数据收集。该间隔还可能影响用于分析的统计方法。例如，时间序列分析通常需要仔细考虑样本间隔，以确保准确识别趋势和模式。如果间隔太宽，重要细节可能会被忽视；如果间隔太窄，数据可能会变得嘈杂且难以解释。研究人员还必须意识到，由于选择的样本间隔引入的潜在偏差。如果该间隔未能反映所研究人群的基本特征，结果可能会失真。例如，如果调查仅在工作日进行，可能无法准确捕捉到在传统工作时间内无法回应的个体的意见。总之，样本间隔是统计研究的一个基本方面，需要谨慎考虑。它不仅影响数据收集过程，还影响研究结果的有效性和可靠性。通过深思熟虑地选择合适的样本间隔，研究人员可以提高研究的质量，并为其领域提供有价值的见解。理解这一概念对于任何参与数据驱动决策的人来说都是必不可少的，因为它为有效分析和解释结果奠定了基础。