derived statistics

简明释义

整理后统计数字

英英释义

例句

1.Using derived statistics, the team was able to identify key performance indicators for the project.

通过使用派生统计数据，团队能够识别项目的关键绩效指标。

2.The dashboard presents real-time derived statistics that allow managers to make informed decisions.

仪表板显示实时的派生统计数据，使管理者能够做出明智的决策。

3.In the analysis, we calculated various derived statistics to assess the effectiveness of the new policy.

在分析中，我们计算了各种派生统计数据以评估新政策的有效性。

4.The report includes several derived statistics, which help in understanding the overall trends in the data.

该报告包含多个派生统计数据，有助于理解数据的整体趋势。

5.Researchers often use derived statistics to summarize complex datasets into more manageable forms.

研究人员经常使用派生统计数据将复杂数据集汇总为更易管理的形式。

作文

In today's data-driven world, the importance of statistics cannot be overstated. Statistics provide a way to summarize and analyze data, allowing us to make informed decisions based on empirical evidence. Among the various types of statistics, derived statistics (派生统计数据) play a crucial role in transforming raw data into meaningful insights. Derived statistics are calculated from raw data to provide more complex or informative metrics that can aid in analysis and understanding. For instance, while raw data might show the number of sales made each day, derived statistics could include averages, trends, or percentages that help businesses understand their performance over time.The process of deriving statistics involves several steps. First, data must be collected from reliable sources. This data can come from surveys, experiments, or existing databases. Once the data is gathered, analysts can begin to manipulate it to create derived statistics (派生统计数据). For example, if a company collects data on customer purchases, they might calculate the average purchase amount per customer, which is a derived statistic (派生统计数据) that provides insight into customer behavior.One of the most common applications of derived statistics (派生统计数据) is in the field of economics. Economists often use these statistics to gauge the health of an economy. For instance, the Gross Domestic Product (GDP) is a derived statistic (派生统计数据) that represents the total value of all goods and services produced in a country within a specific timeframe. By analyzing GDP growth rates, policymakers can make decisions about fiscal policies, taxation, and government spending.Another significant area where derived statistics (派生统计数据) are utilized is in public health. Health organizations track various health indicators, such as disease prevalence rates and vaccination coverage. These raw data points can be transformed into derived statistics (派生统计数据) like incidence rates or risk ratios, which help public health officials understand the effectiveness of health interventions and allocate resources accordingly.Moreover, in the realm of sports analytics, derived statistics (派生统计数据) have revolutionized how teams evaluate player performance. Traditional statistics, such as goals scored or assists, are often insufficient to capture a player's overall impact on the game. Advanced metrics like Player Efficiency Rating (PER) or Wins Above Replacement (WAR) are examples of derived statistics (派生统计数据) that incorporate multiple factors to provide a more comprehensive view of a player's contribution.However, it is essential to approach derived statistics (派生统计数据) with caution. While they can provide valuable insights, they are only as good as the data and methods used to derive them. Misinterpretation or misuse of these statistics can lead to misguided conclusions and poor decision-making. Therefore, it is crucial for analysts and decision-makers to understand the context and limitations of derived statistics (派生统计数据).In conclusion, derived statistics (派生统计数据) are an invaluable tool in various fields, including business, economics, public health, and sports. They allow us to take raw data and transform it into actionable insights that can guide decisions and strategies. As we continue to generate vast amounts of data, the ability to derive meaningful statistics will only become more critical in our quest to understand the world around us.