analyzable

简明释义

英[ˈænəˌlaɪzəbl]美[ˈænəˌlaɪzəbl]

adj. 可分析的

英英释义

单词用法

同义词

反义词

例句

1.The theory of constructivism of western international relation offers new tentative ideation, analyzable frame and solution for the above objectivity.

当代西方国际关系理论中的建构主义为上述实况提供了一种新的思维尝试、分析框架与消解困境的方案补充。

2.Bed thickness is analyzable until the bed thickness is vanishingly small.

可分析的薄层厚度可以无限小，直至消失。

3.EVA, economic profit index, offers measurable and analyzable tool for comprehensive budget management, as a result, it provided with extensive suitability.

经济利润指标EVA为全面预算管理体系提供了测定和分析工具，具有广泛的适用性。

4.No conceptual analysis . Some concepts are analyzable functionally, or in terms of the concepts of physics.

没有概念分析：一些概念是功能上可分析的，或根据物理概念。

5.From the perspective of cognitive metaphor, idioms are found to be analyzable instead of lack of motivation. Metaphorical concept provides motivation for compositional and transparent idioms.

本文运用认知隐喻观着重分析了“可分析显性”习语，发现习语语义并非完全不可预测，隐喻概念为之提供了部分语义理据。

6.Perhaps even some mental concepts can be given functional or physical analyses. But consciousness is not one of these analyzable concepts.

或许，即使有一些精神概念能被功能的或物理的分析，但意识概念不是可分析的。

7.Results All 10 CPT patients specimen after cell culture were analyzable.

结果10例CPT患者的淋巴细胞培养均获得可分析标本。

8.From the perspective of cognitive metaphor, idioms are found to be analyzable instead of lack of motivation. Metaphorical concept provides motivation for compositional and transparent idioms.

本文运用认知隐喻观着重分析了“可分析显性”习语，发现习语语义并非完全不可预测，隐喻概念为之提供了部分语义理据。

9.The function is objective and analyzable. The semantic information of a discourse is of many hiearchies.

言语单位的语义信息功能是客观的，可分析的。

10.We need to ensure that the results are analyzable before we publish them.

在发布结果之前，我们需要确保这些结果是可分析的。

11.His research findings are analyzable using statistical methods.

他的研究结果可以使用统计方法进行分析。

12.This software provides tools to make your reports analyzable.

该软件提供工具，使您的报告变得可分析的。

13.We should focus on creating analyzable metrics for our project.

我们应该专注于为我们的项目创建可分析的指标。

14.The data collected from the survey is fully analyzable.

从调查中收集的数据是完全可分析的。

作文

In today's world, data is everywhere. From social media interactions to online shopping behaviors, we are constantly generating vast amounts of information that can be incredibly valuable if properly understood and utilized. This is where the concept of analyzable (可分析的) data comes into play. Understanding what makes data analyzable is essential for businesses, researchers, and individuals who wish to make informed decisions based on evidence rather than intuition.To begin with, data must be structured in a way that allows it to be easily processed and examined. This means that raw data needs to be cleaned and organized before it can be deemed analyzable (可分析的). For instance, if a company collects customer feedback through surveys, the responses need to be categorized and quantified to identify trends and patterns. Without this step, the data remains a chaotic collection of opinions that cannot be effectively analyzed.Once the data is structured, the next step is to choose the right analytical tools and methods. There are numerous software options available that can help in analyzing data sets, making them more analyzable (可分析的). For example, statistical software like SPSS or R can process complex datasets, enabling users to perform various analyses such as regression or correlation studies. The choice of tools often depends on the type of data and the specific questions that need to be answered.Moreover, the interpretability of results is crucial when dealing with analyzable (可分析的) data. It’s not enough to generate numbers and graphs; one must also be able to explain what these findings mean in a real-world context. For instance, if a business discovers that customer satisfaction scores have dropped, they need to delve deeper into the data to understand why this happened. Was it due to product quality, customer service, or perhaps pricing? Only by interpreting the data correctly can organizations take actionable steps to improve their performance.Furthermore, the importance of having clear objectives cannot be overstated. When data is collected without a specific purpose, it often becomes overwhelming and less analyzable (可分析的). Setting clear goals helps in focusing the analysis on relevant aspects, ensuring that the insights gained are meaningful and applicable. For example, a marketing team might collect data on consumer behavior to understand which advertising channels are most effective. By having a clear objective, they can streamline their data collection and analysis processes.In addition to structured data, the growing field of big data has introduced new challenges and opportunities for analyzable (可分析的) information. With the ability to analyze large volumes of unstructured data from sources like social media or online reviews, organizations can gain deeper insights into consumer sentiments and market trends. However, this also requires advanced analytical skills and tools, as traditional methods may not suffice for such vast datasets.In conclusion, the ability to turn raw information into analyzable (可分析的) data is a vital skill in our data-driven society. Whether for business, research, or personal decision-making, understanding how to collect, structure, and interpret data can lead to more informed choices and better outcomes. As we continue to navigate an increasingly complex information landscape, mastering the art of making data analyzable (可分析的) will undoubtedly be a key factor in achieving success in various fields.

在当今世界，数据无处不在。从社交媒体互动到在线购物行为，我们不断生成大量信息，如果能够正确理解和利用，这些信息将极具价值。这就是“analyzable（可分析的）”数据概念的重要性。理解什么使数据成为analyzable（可分析的）对于希望基于证据而非直觉做出明智决策的企业、研究人员和个人而言至关重要。首先，数据必须以一种易于处理和检查的方式进行结构化。这意味着原始数据需要在被认为是analyzable（可分析的）之前进行清理和组织。例如，如果一家公司通过调查收集客户反馈，则需要对响应进行分类和量化，以识别趋势和模式。如果没有这一步，数据将仍然是混乱的意见集合，无法有效分析。一旦数据结构化，下一步是选择合适的分析工具和方法。有许多软件选项可以帮助分析数据集，使其更具analyzable（可分析的）。例如，SPSS或R等统计软件可以处理复杂的数据集，使用户能够执行各种分析，如回归或相关性研究。工具的选择通常取决于数据类型和需要回答的具体问题。此外，结果的可解释性在处理analyzable（可分析的）数据时至关重要。仅仅生成数字和图表是不够的；还必须能够解释这些发现在现实世界中的意义。例如，如果一家企业发现客户满意度评分下降，他们需要深入分析数据以了解原因。这是由于产品质量、客户服务，还是定价？只有通过正确解释数据，组织才能采取可行步骤来改善业绩。此外，设定明确目标的重要性不容低估。当数据在没有特定目的的情况下收集时，往往会变得压倒性且不那么analyzable（可分析的）。明确的目标有助于集中分析在相关方面，确保获得的见解是有意义且可应用的。例如，营销团队可能会收集有关消费者行为的数据，以了解哪些广告渠道最有效。通过设定明确的目标，他们可以简化数据收集和分析过程。除了结构化数据外，快速发展的大数据领域也为analyzable（可分析的）信息带来了新的挑战和机遇。通过分析来自社交媒体或在线评论的大量非结构化数据，组织可以深入了解消费者情绪和市场趋势。然而，这也需要先进的分析技能和工具，因为传统方法可能不足以应对如此庞大的数据集。总之，将原始信息转化为analyzable（可分析的）数据的能力是在我们数据驱动的社会中必不可少的。无论是为了商业、研究还是个人决策，理解如何收集、结构化和解释数据都可以导致更明智的选择和更好的结果。随着我们继续在日益复杂的信息环境中航行，掌握使数据analyzable（可分析的）艺术无疑将成为在各个领域取得成功的关键因素。