cross-sectional

cross-sectional的音标是[ˌkrɔːs-seɪˈʃenəl]，意思是横断的；横断面的；横切的。基本翻译为“横断面的；横切面的；横截面的”。速记技巧可以使用谐音记忆法，将其转化为容易记忆的读音。例如，可以将“sectional”谐音译为“杀色胎了”。这样可以帮助您快速记住这个单词的发音和含义。

Cross-sectional这个词源自拉丁语，意为“在各个部分之间”。它的变化形式包括复数形式cross-sectional，过去式cross-sectioned，过去分词cross-sectioned和现在分词cross-sectioning。

相关单词：

1. Cross-sectional analysis（横截面分析）：一种统计学方法，用于分析不同个体或群体在不同时间点的样本数据，以揭示其特征和变化趋势。

2. Cross-sectional survey（横截面调查）：一种调查方法，通过收集各个部分或群体的数据来了解某一特定时期或背景下的社会、经济、文化等状况。

3. Cross-sectional inequality（横截面不平等）：在某一特定时间点或背景下的不平等现象，通常用于描述不同个体或群体之间的经济、社会、文化等方面的差异。

横截面分析在经济学、社会学、人口学等领域中有着广泛的应用，它可以帮助我们更好地理解社会现象的多样性和复杂性。同时，横截面调查也是衡量社会变化和评估政策效果的重要手段之一。

常用短语：

1. cross-sectional analysis

2. cross-sectional data

3. cross-sectional survey

4. cross-sectional study

5. cross-sectional design

6. cross-sectional distribution

7. cross-sectional analysis of variance

例句：

1. The data collected in the cross-sectional survey is very useful for analyzing the relationship between variables.

2. The cross-sectional design of this study allows us to examine the impact of various factors on outcomes.

3. The cross-sectional distribution of the population shows that there are significant differences in the distribution of various characteristics across different groups.

4. Cross-sectional analysis of variance was used to examine the differences in performance across different groups.

5. The cross-sectional data suggests that there may be a relationship between the two variables, but further research is needed to confirm this finding.

6. The cross-sectional study provides valuable information about the current state of the problem and can help inform future research directions.

7. The cross-sectional design of this study has limitations in terms of generalizability, but it still provides valuable insights into the phenomenon under investigation.

英文小作文：

Title: Cross-Sectional Analysis: A Tool for Understanding Population Diversity

Cross-sectional analysis is a powerful tool for understanding population diversity and exploring relationships between variables. It allows us to examine patterns of data across a single point in time, providing a snapshot of the current state of affairs. Through cross-sectional analysis, we can gain insights into the distribution of various characteristics across different groups, identify patterns in behavior and outcomes, and examine potential relationships between variables.

However, cross-sectional analysis has limitations, as it only provides a snapshot of a moment in time and may not be generalizable to the entire population. Therefore, it is important to interpret cross-sectional data with caution and use it to inform future research directions rather than make definitive conclusions. Nevertheless, cross-sectional analysis remains an essential tool for gaining a deeper understanding of the complexity of human populations and can help us identify patterns and trends that would otherwise be overlooked.