cross classification; crossed classification

简明释义

交叉分类

英英释义

例句

1.We applied cross classification 交叉分类 to understand how different factors influence employee satisfaction.

我们应用了cross classification 交叉分类来理解不同因素如何影响员工满意度。

2.Using cross classification 交叉分类, we were able to identify patterns in customer preferences across different regions.

通过使用cross classification 交叉分类，我们能够识别出不同地区客户偏好的模式。

3.The report included a cross classification 交叉分类 of survey responses by gender and education level.

报告中包含了按性别和教育水平进行的cross classification 交叉分类的调查响应。

4.The cross classification 交叉分类 method allowed us to segment the market based on age and income levels.

该cross classification 交叉分类方法使我们能够根据年龄和收入水平细分市场。

5.In our research study, we used cross classification 交叉分类 to analyze the effects of diet and exercise on health outcomes.

在我们的研究中，我们使用了cross classification 交叉分类来分析饮食和运动对健康结果的影响。

作文

In the field of statistics, data analysis often requires a nuanced understanding of how different variables interact with one another. One method that is particularly useful in this regard is known as cross classification (交叉分类). This technique allows researchers to categorize data into multiple dimensions, providing a clearer picture of the relationships between variables. For instance, consider a study examining the effectiveness of various teaching methods on student performance across different age groups. By employing cross classification, researchers can analyze how each teaching method affects students of various ages, thus uncovering trends that may not be visible when looking at the data in isolation.The power of cross classification lies in its ability to reveal interactions between categorical variables. When data is classified in such a way, it enables the identification of patterns that might suggest correlations or causations. For example, if we were to cross-classify data based on both gender and academic performance, we might find that one gender performs better in certain subjects. This insight could lead to targeted interventions aimed at supporting students who may be struggling.Another important aspect of cross classification is its application in market research. Businesses often utilize this technique to segment their customer base more effectively. By categorizing consumers according to various demographic factors such as age, income, and purchasing behavior, companies can tailor their marketing strategies to meet the specific needs of each segment. For example, a company selling sports equipment might use cross classification to identify which age group is most likely to purchase running shoes, allowing them to focus their advertising efforts accordingly.Moreover, cross classification can also be beneficial in public health studies. By examining how different health outcomes are distributed across various demographic categories, researchers can identify at-risk populations and develop targeted health interventions. For instance, if a study finds that obesity rates are significantly higher among low-income families within a specific age range, public health officials can implement programs that address the unique challenges faced by these groups.Despite its advantages, cross classification does come with challenges. The complexity of managing multiple variables can lead to difficulties in data interpretation. It is crucial for researchers to ensure that the classifications they create are meaningful and relevant to the questions they are trying to answer. Additionally, there is a risk of overfitting the data if too many categories are created, which can obscure rather than clarify the relationships being studied.In conclusion, cross classification (交叉分类) is a powerful tool in data analysis that enhances our understanding of how different variables interact. Whether in educational research, market analysis, or public health, this technique provides valuable insights that can inform decision-making processes. As researchers continue to explore the complexities of data, mastering methodologies like cross classification will be essential for drawing accurate conclusions and implementing effective solutions.