summary statistics

简明释义

概括统计量

英英释义

例句

1.The summary statistics 汇总统计 revealed that the average score increased over the semester.

该汇总统计 summary statistics 显示平均分在学期内有所上升。

2.The report includes various summary statistics 汇总统计 to help visualize the data trends.

该报告包含各种汇总统计 summary statistics，以帮助可视化数据趋势。

3.The summary statistics 汇总统计 include measures such as mean, median, and standard deviation.

该汇总统计 summary statistics 包括均值、中位数和标准差等指标。

4.We can use summary statistics 汇总统计 to compare the performance of different groups.

我们可以使用汇总统计 summary statistics 来比较不同组的表现。

5.Before diving into the analysis, we should first look at the summary statistics 汇总统计 of the dataset.

在深入分析之前，我们应该首先查看数据集的汇总统计 summary statistics。

作文

In the realm of data analysis, understanding the concept of summary statistics is crucial for interpreting datasets effectively. Summary statistics refers to a set of brief informational coefficients that summarize a given dataset. These statistics provide a quick overview of the main features of the data, allowing researchers and analysts to grasp essential insights without delving into the raw data itself. When dealing with large datasets, it can be overwhelming to sift through all the information. This is where summary statistics come into play. They typically include measures such as the mean, median, mode, range, variance, and standard deviation. Each of these measures serves a unique purpose in understanding the distribution and variability of the data. For instance, the mean provides an average value, offering a central point around which the data clusters. The median, on the other hand, represents the middle value when the data is ordered, which can be particularly useful in skewed distributions where the mean may not accurately reflect the dataset's central tendency. The mode identifies the most frequently occurring value, giving insight into common trends within the data.Range, variance, and standard deviation are essential for understanding how spread out the data points are. The range gives the difference between the maximum and minimum values, while variance and standard deviation quantify the degree of variation or dispersion in the dataset. A low standard deviation indicates that the data points tend to be close to the mean, whereas a high standard deviation signifies that the data points are spread out over a larger range of values. Using summary statistics allows researchers to quickly communicate findings, making it easier to present data in reports or presentations. For example, a business analyst might use summary statistics to report on sales figures, highlighting key metrics such as the average sales per month and the variability in those sales. This information can guide decision-making processes and strategic planning.Moreover, summary statistics are foundational in more complex statistical analyses. They help in identifying patterns, anomalies, or trends in the data that may warrant further investigation. For example, if a dataset shows a significant deviation in the standard deviation compared to previous periods, it could indicate a shift in consumer behavior or market conditions that requires attention.In conclusion, summary statistics are indispensable tools in data analysis that provide a concise overview of key characteristics of a dataset. By summarizing the data, they enable analysts to make informed decisions and derive meaningful insights efficiently. Whether in academic research, business analytics, or any field involving data interpretation, mastering the use of summary statistics is vital for effective communication and analysis.

在数据分析领域，理解summary statistics的概念对于有效解读数据集至关重要。Summary statistics指的是一组简短的信息系数，用于总结给定的数据集。这些统计数据提供了对数据主要特征的快速概述，使研究人员和分析师能够在不深入原始数据的情况下掌握基本见解。在处理大型数据集时，筛选所有信息可能会令人感到不知所措。这就是summary statistics发挥作用的地方。它们通常包括均值、中位数、众数、范围、方差和标准差等度量。每一个度量在理解数据的分布和变异性方面都有独特的用途。例如，均值提供了一个平均值，提供了数据聚集的中心点。而中位数则代表了当数据被排序时的中间值，这在偏斜分布中尤其有用，因为均值可能无法准确反映数据集的中心趋势。众数识别出最常出现的值，从而洞察数据中的常见趋势。范围、方差和标准差对于理解数据点的分散程度至关重要。范围给出了最大值和最小值之间的差，而方差和标准差量化了数据集中数据点的变化或分散程度。较低的标准差表明数据点倾向于接近均值，而较高的标准差则表示数据点分散在更大的值范围内。使用summary statistics使研究人员能够快速传达发现，使得在报告或演示中呈现数据变得更加容易。例如，商业分析师可能会使用summary statistics来报告销售数字，突出关键指标，如每月的平均销售额及其变动性。这些信息可以指导决策过程和战略规划。此外，summary statistics是更复杂统计分析的基础。它们有助于识别数据中的模式、异常或趋势，这些可能需要进一步调查。例如，如果某个数据集的标准差与之前的时期相比显示出显著偏差，这可能表明消费者行为或市场条件发生了变化，需要引起注意。总之，summary statistics是数据分析中不可或缺的工具，提供了数据集关键特征的简明概述。通过总结数据，它们使分析师能够高效地做出明智的决策并得出有意义的见解。无论是在学术研究、商业分析，还是在任何涉及数据解读的领域，掌握summary statistics的使用对于有效沟通和分析至关重要。