sample point

简明释义

抽样点

英英释义

例句

1.In machine learning, a sample point 样本点 refers to an individual data entry used for training the model.

在机器学习中，样本点指的是用于训练模型的单个数据条目。

2.Each sample point 样本点 contributes to the overall understanding of the phenomenon being studied.

每个样本点都有助于对所研究现象的整体理解。

3.When conducting a survey, each sample point 样本点 is crucial for ensuring accurate results.

在进行调查时，每个样本点对确保结果的准确性至关重要。

4.The researcher selected a random sample point 样本点 from the dataset to analyze.

研究人员从数据集中随机选择了一个样本点进行分析。

5.In the field of statistics, a sample point 样本点 represents a single observation from a larger population.

在统计学中，样本点表示来自更大人群的单个观察。

作文

In the world of statistics and data analysis, the term sample point refers to a specific observation or data value that is taken from a larger population. To understand this concept better, let us consider an example involving a survey conducted to assess the average height of students in a school. When researchers want to determine this average, they cannot measure the height of every single student due to time and resource constraints. Instead, they select a smaller group of students, which serves as their sample. Each individual measurement within this group is considered a sample point. The significance of a sample point lies in its contribution to the overall analysis of the population. By analyzing the heights of these selected students, researchers can make educated estimates about the average height of all students in the school. This method relies on the assumption that the sample accurately represents the larger population, which is why careful selection of sample points is crucial. If the sample is biased or unrepresentative, the conclusions drawn may be flawed.Moreover, the concept of a sample point extends beyond just physical measurements. In various fields such as psychology, marketing, and environmental science, researchers often collect data through surveys, experiments, or observations. Each piece of data collected in these studies is a sample point. For instance, in a marketing study aimed at understanding consumer preferences, each respondent's answer to a survey question would represent a sample point. By aggregating these sample points, analysts can identify trends and patterns that inform business strategies.In addition to its practical applications, understanding sample points is essential for interpreting statistical results accurately. For example, when researchers present findings based on a sample, they often use measures such as the mean, median, or mode to summarize the data. These measures are calculated using the sample points collected. Therefore, the quality and reliability of these sample points directly impact the validity of the statistical analysis. If the sample points are not representative, the summary statistics may lead to incorrect conclusions.Furthermore, the concept of sample points is integral to hypothesis testing and inferential statistics. Researchers formulate hypotheses about a population and then use sample points to test these hypotheses. The results of these tests help determine whether the observed effects in the sample can be generalized to the entire population. This process underscores the importance of selecting appropriate sample points to ensure that the findings are robust and applicable.In conclusion, the term sample point is a fundamental concept in statistics that represents individual data values collected from a larger population. Understanding the role of sample points is vital for conducting accurate analyses, drawing valid conclusions, and making informed decisions based on data. Whether in academic research or practical applications, recognizing the significance of each sample point can greatly enhance our understanding of the world around us.

在统计学和数据分析的世界中，术语sample point指的是从较大总体中提取的特定观察值或数据值。为了更好地理解这一概念，让我们考虑一个关于评估学校学生平均身高的调查的例子。当研究人员想要确定这个平均值时，由于时间和资源的限制，他们无法测量每个学生的身高。因此，他们选择了一小部分学生，这部分学生构成了他们的样本。该组内的每个单独测量被视为sample point。sample point的重要性在于它对总体分析的贡献。通过分析这些选定学生的身高，研究人员可以对学校所有学生的平均身高做出有根据的估计。这种方法依赖于样本能够准确代表更大总体的假设，这就是为什么仔细选择sample points至关重要的原因。如果样本存在偏差或不具代表性，那么得出的结论可能是错误的。此外，sample point的概念不仅限于物理测量。在心理学、市场营销和环境科学等多个领域，研究人员通常通过调查、实验或观察收集数据。这些研究中收集的每一条数据都是一个sample point。例如，在一项旨在了解消费者偏好的市场研究中，每位受访者对调查问题的回答将代表一个sample point。通过聚合这些sample points，分析师可以识别出影响商业策略的趋势和模式。除了其实际应用之外，理解sample points对于准确解释统计结果至关重要。例如，当研究人员基于样本呈现发现时，他们通常使用均值、中位数或众数等指标来总结数据。这些指标是通过收集的sample points计算得出的。因此，这些sample points的质量和可靠性直接影响统计分析的有效性。如果sample points不具代表性，则汇总统计可能会导致错误的结论。此外，sample points的概念对于假设检验和推断统计学至关重要。研究人员对总体提出假设，然后使用sample points来检验这些假设。这些测试的结果有助于确定样本中观察到的效应是否可以推广到整个总体。这一过程强调了选择适当的sample points以确保研究结果稳健且适用的重要性。总之，术语sample point是统计学中的一个基本概念，代表从较大总体中收集的个体数据值。理解sample points的作用对于进行准确分析、得出有效结论以及基于数据做出明智决策至关重要。无论是在学术研究还是实际应用中，认识到每个sample point的重要性都能极大增强我们对周围世界的理解。