contingency table

简明释义

相依表［质量管理］

英英释义

例句

1.To evaluate the effectiveness of the new drug, a contingency table (列联表) was constructed to compare treatment outcomes.

为了评估新药的有效性，构建了一个contingency table (列联表) 来比较治疗结果。

2.In our statistics class, we learned how to create a contingency table (列联表) to analyze the relationship between two categorical variables.

在我们的统计课上，我们学习了如何创建一个contingency table (列联表) 来分析两个分类变量之间的关系。

3.The researchers used a contingency table (列联表) to summarize the survey results and identify patterns in the data.

研究人员使用contingency table (列联表) 来总结调查结果并识别数据中的模式。

4.By examining the contingency table (列联表), we could see that there was a significant association between education level and employment status.

通过检查contingency table (列联表)，我们可以看到教育水平和就业状态之间存在显著关联。

5.The marketing team created a contingency table (列联表) to analyze customer preferences based on age and gender.

市场团队创建了一个contingency table (列联表) 来分析基于年龄和性别的客户偏好。

作文

In the field of statistics, a contingency table is a powerful tool used to analyze the relationship between two or more categorical variables. This table allows researchers to observe the frequency distribution of variables and assess how they interact with one another. For instance, consider a study examining the relationship between smoking habits and lung cancer occurrence. By creating a contingency table, researchers can categorize individuals based on their smoking status (smoker or non-smoker) and whether they have been diagnosed with lung cancer (yes or no). The resulting table provides a clear visual representation of the data, making it easier to identify patterns and correlations.The structure of a contingency table typically consists of rows and columns, where each cell represents the count of observations that fall into the corresponding categories. For example, in our smoking and lung cancer study, one cell might represent the number of smokers who have lung cancer, while another cell might show the number of non-smokers without lung cancer. This setup not only helps in organizing the data but also facilitates further statistical analysis, such as calculating probabilities and conducting chi-square tests.Understanding how to construct and interpret a contingency table is essential for anyone involved in data analysis. It enables researchers to summarize complex data sets efficiently and derive meaningful insights. Moreover, the use of contingency tables is not limited to health studies; they are widely applicable in various fields, including social sciences, marketing, and education. For instance, a company may use a contingency table to analyze customer preferences based on age groups and product types, helping them tailor their marketing strategies effectively.One of the key advantages of using a contingency table is its ability to reveal associations between variables. By examining the proportions within the table, researchers can identify whether certain categories are more likely to co-occur than others. This aspect is particularly useful when testing hypotheses. For example, if the proportion of lung cancer cases is significantly higher among smokers compared to non-smokers, it supports the hypothesis that smoking is a risk factor for lung cancer.However, it is crucial to be cautious when interpreting the results from a contingency table. Correlation does not imply causation, and other confounding variables may influence the observed relationships. Therefore, while contingency tables provide valuable insights, they should be complemented with additional analyses and contextual understanding.In conclusion, a contingency table serves as an indispensable tool for analyzing categorical data and uncovering relationships between variables. Its structured format allows for clear visualization and interpretation of data, making it easier for researchers to draw conclusions and make informed decisions. As we continue to gather vast amounts of data in various domains, mastering the use of contingency tables will remain a critical skill for statisticians and researchers alike.

在统计学领域，列联表是用于分析两个或多个分类变量之间关系的强大工具。这个表格允许研究人员观察变量的频率分布，并评估它们之间的相互作用。例如，考虑一个研究吸烟习惯与肺癌发生之间关系的案例。通过创建一个列联表，研究人员可以根据个体的吸烟状态（吸烟者或非吸烟者）以及是否被诊断为肺癌（是或否）对个体进行分类。最终得到的表格提供了数据的清晰视觉表示，使得识别模式和相关性变得更加容易。列联表的结构通常由行和列组成，其中每个单元格代表落入相应类别的观察数量。例如，在我们的吸烟与肺癌研究中，一个单元格可能代表患有肺癌的吸烟者的数量，而另一个单元格可能显示没有肺癌的非吸烟者的数量。这种设置不仅有助于组织数据，还促进了进一步的统计分析，例如计算概率和进行卡方检验。理解如何构建和解释列联表对于任何参与数据分析的人来说都是至关重要的。它使研究人员能够高效地总结复杂的数据集并得出有意义的见解。此外，列联表的使用并不限于健康研究；它们在社会科学、市场营销和教育等多个领域广泛适用。例如，一家公司可能会使用列联表来分析基于年龄组和产品类型的客户偏好，从而帮助他们有效地调整营销策略。使用列联表的一个主要优点是它能够揭示变量之间的关联。通过检查表中的比例，研究人员可以确定某些类别是否比其他类别更可能共同出现。这一方面在检验假设时特别有用。例如，如果吸烟者的肺癌病例比例明显高于非吸烟者，这支持了吸烟是肺癌风险因素的假设。然而，在解释列联表的结果时必须谨慎。相关性并不意味着因果关系，其他混杂变量可能会影响观察到的关系。因此，尽管列联表提供了宝贵的见解，但它们应该与额外的分析和上下文理解相结合。总之，列联表作为分析分类数据和揭示变量之间关系的重要工具，其结构化格式允许对数据进行清晰的可视化和解释，使研究人员更容易得出结论并做出明智的决策。随着我们在各个领域继续收集大量数据，掌握列联表的使用将仍然是统计学家和研究人员的关键技能。