statistical tabulation

简明释义

编制统计表

英英释义

例句

1.For the project, we need a statistical tabulation 统计表格 of the last five years' sales data.

对于这个项目，我们需要过去五年销售数据的统计表格 统计表格。

2.The government released a statistical tabulation 统计表格 on employment rates across different sectors.

政府发布了一份关于各个行业就业率的统计表格 统计表格。

3.The statistical tabulation 统计表格 of crime rates helped local authorities allocate resources more effectively.

犯罪率的统计表格 统计表格帮助地方当局更有效地分配资源。

4.In our annual report, we included a statistical tabulation 统计表格 of customer demographics.

在我们的年度报告中，我们包含了客户人口统计的统计表格 统计表格。

5.The researcher conducted a thorough statistical tabulation 统计表格 of the survey results to identify trends.

研究人员对调查结果进行了彻底的统计表格 统计表格，以识别趋势。

作文

In the modern world, data is everywhere. From business analytics to social sciences, the ability to collect and analyze data has become crucial for making informed decisions. One of the fundamental processes in data analysis is statistical tabulation, which refers to the systematic arrangement of data in tables to facilitate understanding and interpretation. This method allows researchers and analysts to summarize large volumes of data in a structured format, making it easier to identify trends, patterns, and relationships within the data. The importance of statistical tabulation cannot be overstated. In various fields such as economics, healthcare, and education, data is collected from numerous sources. For instance, in healthcare, patient data is often collected in surveys or clinical trials. By employing statistical tabulation, healthcare professionals can organize this data into tables that display key metrics such as patient demographics, treatment outcomes, and side effects. This organized presentation not only aids in analysis but also enhances communication among stakeholders, including doctors, researchers, and policymakers.Moreover, statistical tabulation plays a pivotal role in decision-making processes. For businesses, understanding customer behavior is essential for developing effective marketing strategies. By analyzing sales data through statistical tabulation, companies can identify their best-selling products, peak sales periods, and customer preferences. This information is invaluable for tailoring marketing campaigns and optimizing inventory management. In addition to its practical applications, statistical tabulation also serves an educational purpose. Students and researchers learning about statistics are often introduced to the concept of tabulating data early in their studies. This foundational skill helps them grasp more complex statistical analyses later on. For example, when students learn to create frequency tables or cross-tabulations, they develop a clearer understanding of how different variables interact with one another. Furthermore, the rise of technology has transformed the way we approach statistical tabulation. With the advent of software tools and applications, creating and managing data tables has become more efficient and accessible. Programs like Excel, SPSS, and R provide users with the ability to manipulate large datasets effortlessly. As a result, even individuals with limited statistical training can perform statistical tabulation and derive meaningful insights from their data. However, it is important to recognize that while statistical tabulation is a powerful tool, it is not without its challenges. One of the main issues is ensuring data quality and accuracy. If the data being tabulated is flawed or biased, the conclusions drawn from the tables may lead to incorrect interpretations. Therefore, it is essential for analysts to implement rigorous data collection and validation processes before engaging in statistical tabulation. In conclusion, statistical tabulation is a vital process in the realm of data analysis, offering numerous benefits across various fields. By systematically organizing data into tables, analysts can uncover insights that drive decision-making and enhance understanding. As technology continues to evolve, the methods and tools for statistical tabulation will likely become even more sophisticated, further empowering individuals and organizations to harness the power of data. The effective use of statistical tabulation will undoubtedly remain a cornerstone of data analysis for years to come.

在现代社会，数据无处不在。从商业分析到社会科学，收集和分析数据的能力已成为做出明智决策的关键过程。统计制表是数据分析中的一个基本过程，指的是将数据系统性地排列成表格，以便于理解和解释。这种方法使研究人员和分析师能够以结构化的格式总结大量数据，从而更容易识别数据中的趋势、模式和关系。统计制表的重要性不容小觑。在经济学、医疗保健和教育等各个领域，数据通常来自多个来源。例如，在医疗保健中，患者数据通常通过调查或临床试验进行收集。通过采用统计制表，医疗专业人员可以将这些数据组织成显示关键指标的表格，如患者人口统计、治疗结果和副作用。这种有组织的呈现不仅有助于分析，还增强了利益相关者之间的沟通，包括医生、研究人员和政策制定者。此外，统计制表在决策过程中也发挥着关键作用。对于企业来说，了解客户行为对于制定有效的营销策略至关重要。通过分析销售数据，企业可以识别出最佳销售产品、销售高峰期和客户偏好。此信息对量身定制营销活动和优化库存管理非常宝贵。除了其实际应用外，统计制表还具有教育意义。学习统计学的学生和研究人员通常在学习初期就接触到制表的概念。这项基础技能帮助他们在后续学习中掌握更复杂的统计分析。例如，当学生学习创建频率表或交叉表时，他们对不同变量之间的相互作用有了更清晰的理解。此外，科技的崛起改变了我们对统计制表的处理方式。随着软件工具和应用程序的出现，创建和管理数据表格变得更加高效和可及。像Excel、SPSS和R这样的程序使用户能够轻松操作大型数据集。因此，即使是统计培训有限的个人，也可以执行统计制表并从数据中得出有意义的见解。然而，必须认识到，虽然统计制表是一种强大的工具，但它也面临挑战。主要问题之一是确保数据的质量和准确性。如果被制表的数据存在缺陷或偏见，则从表格中得出的结论可能导致错误的解释。因此，分析师在进行统计制表之前，必须实施严格的数据收集和验证流程。总之，统计制表是数据分析领域中的一项重要过程，在各个领域提供了众多好处。通过将数据系统性地组织成表格，分析师可以发现推动决策和增强理解的见解。随着技术的不断发展，统计制表的方法和工具可能会变得更加复杂，进一步赋予个人和组织利用数据的能力。有效使用统计制表无疑将继续成为未来数据分析的基石。